JP2022027933A - Information generation device, information presentation system, and information generation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide evaluations pertaining to sale and purchase data of investment commodities.

SOLUTION: A server (30) includes an information generation unit (3021) for acquiring transaction data of investment commodities, creating aggregation object by investment target transaction data in which transaction data are classified for each investment target, creating, using the aggregation object by investment target transaction data, unrealized profit/loss level transaction data for each investment target that constitutes the source of unrealized profits/losses which is one of level-classified profits/losses, in accordance with the transaction state of investment commodities included in each investment target, calculating an evaluation index for evaluating an unrealized profit/loss which is one of level-classified profits/losses from the unrealized profit/loss level transaction data, and generating evaluation information of unrealized profit/loss per investment target, using the evaluation index.

SELECTED DRAWING: Figure 20

COPYRIGHT: (C)2022,JPO&INPIT

Description

The present invention relates to an information generation device, an information presentation system, and an information generation program.

Conventionally, a system that advises individual investors has been known. For example, Patent Document 1 discloses financial investment management, portfolio management, educational and analytical tools for members via an internet site.

Special Table 2003-531444 (published on October 21, 2003, internationally published on October 25, 2001)

There are tools for evaluating and diagnosing static portfolios and stocks, but at present, we acquire investor trading data and evaluate dynamically changing trading data based on the investor's trading data. There is no tool to diagnose, compare and advise.

Despite the fact that buying and selling is a factor of investor disparity, there is currently no service to evaluate, diagnose, compare and advise on it.

In the past, sales positions of securities companies, as a free service, have made proposals for improving the current situation while comparing it with other customers based on the trading data of individual investors. On the other hand, in recent years, due to the spread of securities trading via the Internet, the above problems have been further solved as a result of the loss of functions such as proposals, diagnosis, and comparison with others from securities companies that have trading data, especially in online securities. It seems to have become prominent.

As a result of not being able to compare and grasp the current situation and losing the advice function, the investment disparity of individual investors has widened and speculative trading has been promoted. The current situation is that it is not suitable for investment. Investors are confused because they don't know what to buy or sell.

One aspect of the present invention is to provide an evaluation of trading data of investment products.

In order to solve the above problems, the information generation device according to one aspect of the present invention is an information generation device that generates information regarding the evaluation of the profit and loss of an investment product by an investor, and acquires trading data of the investment product. Then, create the aggregated trading data by investment target that classifies the above trading data for each investment target, and use the aggregated trading data by investment target according to the trading status of the above investment products included in each investment target. For each investment target, create unrealized gain / loss level trading data that is the source of unrealized gain / loss, which is one of the leveled gains / losses, and from the above unrealized gain / loss level trading data, unrealized gain / loss, which is one of the leveled gains / losses. It is provided with an information generation unit that calculates an evaluation index for evaluation and generates evaluation information of unrealized gains / losses for each investment target using the evaluation index.

In order to solve the above problems, the information generation device according to one aspect of the present invention is an information generation device that generates information regarding the evaluation of the profit and loss of an investment product by an investor, and acquires trading data of the investment product. Then, create the aggregated trading data by investment target that classifies the above trading data for each investment target, and use the aggregated trading data by investment target according to the trading status of the above investment products included in each investment target. For each investment target, create trading profit / loss level trading data that is the source of trading profit / loss, which is one of the leveled profit / loss, and from the above trading profit / loss level trading data, the trading profit / loss, which is one of the leveled profit / loss, is calculated. It is provided with an information generation unit that calculates an evaluation index for evaluation and generates evaluation information of trading profit / loss for each investment target by using the evaluation index.

According to one aspect of the present invention, it is possible to provide an evaluation regarding trading data of investment products.

It is a figure which shows the hardware composition of the advice presentation system which concerns on Embodiment 1 of this invention. It is a block diagram which shows the structure of the terminal and the server which concerns on Embodiment 1 of this invention. It is a figure which shows the processing outline of the advice presentation system which concerns on Embodiment 1 of this invention. (A) is a diagram showing an example of trading data of investment products according to the first embodiment of the present invention, and (b) is a diagram showing an example of an evaluation index of trading data according to the first embodiment of the present invention. It is a flowchart which shows the diagnostic process by the principal rotation period which concerns on Embodiment 1 of this invention. It is a flowchart which shows the diagnostic process by the winning rate of return which concerns on Embodiment 1 of this invention. It is a flowchart which shows the diagnostic process by the loss loss rate which concerns on Embodiment 1 of this invention. It is a flowchart which shows the diagnosis process by the trading profit and loss which concerns on Embodiment 1 of this invention. It is a flowchart which shows the classification process of the buying and selling pattern which concerns on Embodiment 1 of this invention. It is a flowchart which shows the diagnostic process by the rate of increase / decrease of the holding brand which concerns on Embodiment 1 of this invention. It is a flowchart which shows the ranking process by the principal increase / decrease rate which concerns on Embodiment 1 of this invention. It is a flowchart which shows the process of the total profit and loss analysis which concerns on Embodiment 1 of this invention. It is a figure which shows the example of the evaluation numerical value of the total profit / loss, the trading profit / loss, and the unrealized profit / loss according to the detail degree which concerns on Embodiment 1 of this invention. It is a figure which shows the example of the evaluation index of the possession product which concerns on Embodiment 1 of this invention. It is a figure which shows the example of the pattern of the possession product which concerns on Embodiment 1 of this invention. It is a figure which shows the example of the initial screen of the stock investment simulation which concerns on Embodiment 2 of this invention. It is a figure which shows the example of the question screen of the stock investment simulation which concerns on Embodiment 2 of this invention. It is a figure which shows the transition of the stock price in the stock investment simulation which concerns on Embodiment 2 of this invention. It is a figure which shows the transition of the evaluation value for each branch of each question in the stock investment simulation which concerns on Embodiment 2 of this invention. It is a figure which shows the structure of the information presentation system which concerns on Embodiment 4 of this invention. It is a figure which shows the contrast of the method of the evaluation process which concerns on Embodiment 4 of this invention. It is a figure for demonstrating the aggregated trading data by period which concerns on Embodiment 4 of this invention. It is a figure which shows the trading data to be aggregated by period which concerns on Embodiment 4 of this invention. It is a figure which shows the procedure of evaluation change which concerns on Embodiment 4 of this invention. It is a figure which shows the example of the change processing to the data by period of the trading profit / loss trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the example of the change processing to the data by period of the trading profit / loss trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the procedure of revaluation of the unrealized profit / loss trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the table example of the trading data to be aggregated by the investor which concerns on Embodiment 4 of this invention. It is a figure which shows the table example of the aggregated trading data by investment object which concerns on Embodiment 4 of this invention. It is a figure which shows the difference between the trading data which is aggregated by profit and loss and profit and loss level trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the difference between the process of the old method and the new method of the trading data to be aggregated by profit and loss which concerns on Embodiment 4 of this invention. It is a figure which shows 5 methods of the evaluation method which concerns on Embodiment 4 of this invention. It is a figure which shows the example which extracted (or classified, aggregated, processed) the trading profit / loss level trading data which concerns on Embodiment 4 of this invention (the trading profit / loss level trading data of FIG. 26 is processed). It is a figure which shows the relationship (not including cash) of the trading profit / loss and unrealized profit / loss which concerns on Embodiment 4 of this invention. It is a figure which shows the relationship (including cash) of the trading profit / loss and unrealized profit / loss which concerns on Embodiment 4 of this invention. It is a figure which shows the breakdown of the evaluation value and the opportunity loss of the profit and loss trading data by period which concerns on Embodiment 4 of this invention. It is a figure which shows the relationship between the trading profit / loss which concerns on Embodiment 4 of this invention, cash, and unrealized profit / loss. It is a figure which shows the extraction of the data of the winning profit level which concerns on Embodiment 4 of this invention. It is a figure which shows the extraction of the data of the winning profit level which concerns on Embodiment 4 of this invention. It is a figure which shows the processing data (new method) of FIG. 38 in Embodiment 4 of this invention. It is a figure which is calculated step by step from the profit and loss level trading data which concerns on Embodiment 4 of this invention. It is a figure which is calculated step by step from the profit and loss level trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the calculation of the profit and loss level stage evaluation index which concerns on Embodiment 4 of this invention. It is a conceptual diagram of the 2nd level (trading profit / loss level trading data) which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the 2nd level (trading profit / loss level trading data) which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the 2nd level (unrealized profit / loss level) which concerns on Embodiment 4 of this invention. It is a figure which shows the effect of the leverage effect and the compound interest effect which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the aggregation target comparison process which concerns on Embodiment 4 of this invention. It is a figure which shows the component comparison process which concerns on Embodiment 4 of this invention. It is explanatory drawing of the profit and loss level evaluation index comparison process which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the ranking explanation which concerns on Embodiment 4 of this invention. It is explanatory drawing of the component ranking which concerns on Embodiment 4 of this invention (in the case where an investor and a stock are aggregate targets). It is a figure which shows the specific example of the multi-layer type ranking which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the aggregation target ranking which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the ranking for each multi-layered aggregation target which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the ranking by profit and loss level which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the interlocking unrealized profit / loss level trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the buying and selling data of the winning pattern 1 level which concerns on Embodiment 4 of this invention. It is a figure which shows the example of the unrealized profit / loss pattern level trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the interlocking unrealized profit / loss level trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the specific example of the buying and selling data of the winning pattern 1 level which concerns on Embodiment 4 of this invention. It is a figure which shows the example of the winning pattern which concerns on Embodiment 4 of this invention. It is a figure which shows three comparison processes which concerns on Embodiment 4 of this invention. It is an information flow chart of a client and a server which concerns on Embodiment 4 of this invention. It is a figure which shows that the generation of the investment subject and the article which concerns on Embodiment 4 of this invention is synonymous with the result of the advice generation system. It is a figure which shows what kind of data is accumulated which concerns on Embodiment 4 of this invention. It is a figure which shows the process using the hardware resource which concerns on Embodiment 4 of this invention. It is a figure which shows the processing method of the information processing system which concerns on Embodiment 4 of this invention. It is a figure which shows the flow of the process of the server of the information processing system which concerns on Embodiment 4 of this invention. It is a figure which shows the processing method 2 of the information processing system which concerns on Embodiment 4 of this invention. It is a figure which shows the calculation processing program of the information processing system which concerns on Embodiment 4 of this invention. It is a figure which shows the data structure of the information processing system which concerns on Embodiment 4 of this invention. It is a figure which shows the reference table system of the information processing system which concerns on Embodiment 4 of this invention. It is a figure which shows the AI machine learning process of the information processing process which concerns on Embodiment 4 of this invention. It is a figure which shows the reference figure of the display table which concerns on Embodiment 4 of this invention. It is a figure which shows the summary of the process of the buying and selling data which concerns on Embodiment 4 of this invention. It is a figure which shows the flow to the evaluation step of the information processing process which concerns on Embodiment 4 of this invention. It is a figure which shows the evaluation index determination step which concerns on Embodiment 4 of this invention. It is a figure which shows the evaluation index importance degree judgment display step which concerns on Embodiment 4 of this invention. It is a figure which shows the evaluation index importance degree determination process which concerns on Embodiment 4 of this invention. It is a figure which shows the evaluation index importance degree determination process 2 which concerns on Embodiment 4 of this invention. It is a figure which shows the machine learning model of the evaluation index importance degree determination process which concerns on Embodiment 4 of this invention. It is a figure which shows the evaluation index importance degree determination process 2 which concerns on Embodiment 4 of this invention. It is a figure which shows the generation display step of the ranking article which concerns on Embodiment 4 of this invention. It is a figure which shows the identification and the market value evaluation process of the unopposed trading data which concerns on Embodiment 4 of this invention. It is a figure which shows the method of taking in the investment product price which concerns on Embodiment 4 of this invention. It is a figure which shows the creation of the trading data to be aggregated by period which concerns on Embodiment 4 of this invention. It is a notation diagram of the interlocking possession situation evaluation which concerns on Embodiment 4 of this invention. It is a figure which shows the table reference system of the information processing process which concerns on Embodiment 4 of this invention. It is a figure which shows the network which concerns on Embodiment 4 of this invention. It is a database-related figure which concerns on Embodiment 4 of this invention. It is a figure which shows the related figure of AI learning which concerns on Embodiment 4 of this invention. It is a figure which shows the relationship of the table reference which concerns on Embodiment 4 of this invention. It is a figure which shows the input form method (transaction data) which concerns on Embodiment 4 of this invention. It is a detailed diagram 1st phase diagram of AI learning which concerns on Embodiment 4 of this invention. It is a detailed diagram 2nd phase diagram of AI learning which concerns on Embodiment 4 of this invention. It is a detailed diagram 3rd phase diagram of AI learning which concerns on Embodiment 4 of this invention. It is a detailed diagram 4th phase diagram of AI learning which concerns on Embodiment 4 of this invention. It is a table of the data to be aggregated by period which concerns on Embodiment 4 of this invention. It is a summary diagram of FIGS. 24 to 26 according to the fourth embodiment of the present invention. It is explanatory drawing of the 1st phase which concerns on Embodiment 4 of this invention. It is explanatory drawing of the 2nd phase to the 4th phase which concerns on Embodiment 4 of this invention. It is a verification chart figure of the brand selection which concerns on Embodiment 4 of this invention. It is a verification chart figure of the brand purchase time which concerns on Embodiment 4 of this invention. It is a stock investment trend chart of another investor during the holding period which concerns on Embodiment 4 of this invention. It is a stock investment trend chart of another investor during the holding period which concerns on Embodiment 4 of this invention. It is explanatory drawing of the calculation step of the evaluation index which concerns on Embodiment 4 of this invention. It is explanatory drawing of the synthesis table of the purchase data and the sale data which concerns on Embodiment 4 of this invention. It is a leverage effect and compound interest effect diagram which concerns on Embodiment 4 of this invention. It is explanatory drawing of the plurality of methods of calculation of the evaluation index which concerns on Embodiment 4 of this invention. It is a calculation table figure of the evaluation index which concerns on Embodiment 4 of this invention.

[Embodiment 1]
Hereinafter, Embodiment 1 of the present invention will be described in detail. The contents of the diagnostic results, advice, and the like shown below are merely examples, and do not limit the present invention.

(Advice presentation system 1)
The advice presentation system (information presentation system) 1 according to the present embodiment will be described with reference to the drawings. FIG. 1 is a diagram showing a hardware configuration of the advice presentation system 1 according to the present embodiment. As shown in FIG. 1, the advice presentation system 1 includes a terminal (terminal device) 2 and a server (information generation device) 3. The terminal 2 and the server 3 are configured to be communicable via the network 4.

The terminal 2 acquires trading data by user operation, reading from a recording medium, or the like, and displays advice according to the trading data, such as a PC, a tablet terminal, or a smartphone. The server 3 generates advice on buying and selling investment products. The network 4 is a network including the Internet. Investment products include stocks (including Japanese stocks and overseas stocks), investment trusts, exchange-traded funds (ETFs), and foreign exchange margin trading (FX).

FIG. 2 is a block diagram showing the configurations of the terminal 2 and the server 3 according to the present embodiment.

(Terminal 2)
As shown in FIG. 2, the terminal 2 includes a communication unit 21, a control unit 22, a display unit 23, and an operation reception unit 24. The communication unit 21 is a unit that communicates with the server 3. The control unit 22 controls the entire terminal 2, and is, for example, one or a plurality of processors. The display unit 23 displays data according to the instructions of the control unit 22, and is, for example, a liquid crystal display. The operation receiving unit 24 receives the user's operation, and is, for example, a keyboard, a mouse, a touch panel, or the like.

(Server 3)
As shown in FIG. 2, the server 3 includes a communication unit 31, a control unit 32, and a storage unit 33. The communication unit 31 is a unit that communicates with the terminal 2. The control unit 32 controls the entire server 3, for example, one or a plurality of processors. The storage unit 33 stores data according to the instructions of the control unit 22, and is, for example, a hard disk device, a flash memory, or the like.

The control unit 32 includes an advice generation unit (information generation unit) 321. The advice generation unit 321 acquires trading data of investment products, acquires basic data from the acquired trading data, calculates an evaluation index with reference to the acquired basic data, and generates information indicating the calculated evaluation index. .. Next, the advice generation unit 321 makes a diagnosis with reference to the evaluation index, and generates information indicating the result of the diagnosis. Then, the advice generation unit 321 generates information indicating advice according to the result of the diagnosis.

The evaluation here means to calculate and evaluate each index from the trading data, and the diagnosis means to diagnose what kind of trading has been done based on those indexes, and advice. Refers to giving advice based on the evaluation result and the diagnosis result. However, the process of evaluation, diagnosis, and advice is not essential and may be provided separately.

Further, the advice generation unit 321 may acquire the total profit / loss from the trading data, calculate the evaluation index with reference to the total profit / loss, and generate information indicating the calculated evaluation index. Next, the advice generation unit 321 acquires the total trading profit / loss and the total unrealized profit / loss from the trading data, calculates the evaluation index by referring to the total trading profit / loss and the total unrealized profit / loss, and generates information indicating the calculated evaluation index. You may. Then, the advice generation unit 321 acquires the total winning profit, the total losing loss, and the total unrealized profit / loss from the trading data, and calculates and calculates the evaluation index by referring to the total winning profit, the total losing loss, and the total unrealized profit / loss. Information indicating an evaluation index may be generated.

Further, the advice generation unit 321 acquires the traded data from the trading data, classifies the trading data into patterns according to the bid price, the selling price, and the market price after the sale, and calculates the total profit / loss for each pattern. The evaluation index may be calculated by referring to the total profit / loss for each pattern, and information indicating the calculated evaluation index may be generated. The market price after the sale indicates the market price after a certain period after the sale, and includes, for example, the market price three months after the sale, the market price one year later, the market price at the time of evaluation, and the like. The terminal 2 presents the information generated by the advice generation unit 321 to the user.

In addition, the advice generation unit 321 calculates an evaluation index with reference to trading data, compares and ranks investors with reference to the calculated evaluation index, and uses information indicating the comparison and ranking of the investors as an evaluation index. May be generated as. The comparison here refers to comparing the evaluation index of the investor with the evaluation index of another investor, the average value of the evaluation index, and the like.

(Outline of processing of advice presentation system 1)
FIG. 3 is a diagram showing an outline of processing of the advice presentation system 1 according to the present embodiment. The processing outline of the advice presentation system 1 will be described with reference to FIG.

(Step S301)
In the terminal 2, the control unit 22 acquires the trading data of the investment product from the operation receiving unit 24 and the like, and the communication unit 21 transmits the trading data to the server 3. Details of the trading data will be described separately.

(Step S302)
In the server 3, the control unit 32 receives the trading data from the terminal 2 by the communication unit 31. The advice generation unit 321 calculates an evaluation index from trading data. The control unit 32 transmits the evaluation index calculated by the communication unit 31 to the terminal 2 as an evaluation result. Details of the evaluation index will be described separately.

(Step S303)
In the terminal 2, the control unit 22 receives the evaluation result from the server 3 by the communication unit 21, and causes the display unit 23 to display the evaluation result.

(Step S304)
In the server 3, the advice generation unit 321 diagnoses the user's buying and selling tendency from the evaluation index calculated in step S302. The control unit 32 transmits the diagnosed trading tendency as a diagnosis result to the terminal 2 by the communication unit 31.

(Step S305)
In the terminal 2, the control unit 22 receives the diagnosis result from the server 3 by the communication unit 21, and causes the display unit 23 to display the diagnosis result.

(Step S306)
In the server 3, the advice generation unit 321 compares and ranks investors from the evaluation index calculated in step S302. The control unit 32 transmits the comparison data and the ranking data of the investor to the terminal 2 by the communication unit 31.

(Step S307)
In the terminal 2, the control unit 22 receives the investor comparison data and the ranking data from the server 3 by the communication unit 21, and causes the display unit 23 to display the investor comparison and ranking.

(Step S308)
In the server 3, the advice generation unit 321 generates advice on the buying and selling of the investment product by referring to the trading data of the investment product, the evaluation index, the tendency of the user to buy and sell, the comparison data of the investors, the ranking data and the like. The control unit 32 transmits the generated advice to the terminal 2 by the communication unit 31.

(Step S309)
In the terminal 2, the control unit 22 receives advice regarding the buying and selling of investment products from the server 3 by the communication unit 21, and displays the advice on the display unit 23.

In the server 3, the calculation of the evaluation index, the storage in the DB, the creation of the diagnostic data, and the storage in the DB, which are performed with reference to the trading data to be evaluated, are executed by, for example, batch processing. .. The DB is set in the storage unit 33 of the server 3, for example.

(Example of trading data)
FIG. 4A is a diagram showing an example of trading data of investment products according to the present embodiment. Hereinafter, stocks will be described as an example of investment products. As shown in FIG. 4A, the trading data includes the stock code, the number of shares purchased, the purchase date, and the bid price. The sold data also includes the date of sale and the selling price. In addition, the trading data when entering from selling (for example, when performing margin trading or the like) includes the stock code, the number of shares sold, the date of sale, and the selling price. The repurchased data further includes the repurchase date and the repurchase value.

The stock code is a code that identifies the stock of the stock to be bought and sold. The number of purchased shares is the number of shares purchased by the user. The purchase date is the date on which the user purchased the shares. The bid price is the stock price when the user purchases the stock. The sale date is the date on which the user sold the shares. The selling price is the stock price when the user sells the stock.

(Example of evaluation index)
FIG. 4B is a diagram showing an example of an evaluation index of trading data according to the present embodiment. Hereinafter, stocks will be described as an example of investment products. As shown in FIG. 4B, the evaluation index is calculated by a plurality of evaluation axes. Examples of the evaluation index include turning power, winning rate of return, losing loss rate, trading profit / loss, rate of increase / decrease of owned stocks, rate of increase / decrease in principal, and the like.

The basic numerical values described later refer to numerical values obtained from trading data such as principal, elapsed period, and number of trades. The evaluation index refers to an index calculated from those basic numerical values and the like. The evaluation axis refers to a cut for evaluating trading data, and is composed of a single evaluation index or a plurality of evaluation indexes.

To give an example of the evaluation axis, the rotational force is an evaluation axis that indicates how fast the user is rotating the principal, in other words, how often the user is replacing the brand. This is just one example. Indicators related to rotational force include average holding period, number of principal rotations, principal rotation period, average trading period difference, and the like. The rotational force index is an index for evaluating, comparing, diagnosing, and giving advice on how often a person buys or sells.

The average holding period is the average holding period of trading stocks. The number of rotations of the principal is an index showing the number of rotations of the principal in a predetermined period, and is calculated by "trading price ÷ principal in a predetermined period". The principal rotation period is an average value of the period during which the principal rotates once, and is calculated by "the number of days in a predetermined period ÷ the number of principal rotations". The average trading period difference is calculated by "average trading period in case of winning-average trading period in case of losing".

The rate of return, which is an example of the evaluation axis, is an example of the evaluation axis that shows the rate of return in the case of a win. It is calculated by "trading price". The profit amount per win is calculated by "total profit amount / number of wins". The trading value per win is calculated by "total trading value in case of winning / number of wins". The rate of return on winning is an example of an evaluation axis for evaluating, comparing, and diagnosing winning patterns, and giving advice on how to win.

The losing loss rate, which is an example of the evaluation axis, is an example of the evaluation axis showing the loss rate in the case of losing. It is calculated by "trading price". The amount of loss per loss is calculated by "total loss amount / number of losses". The trading value per loss is calculated by "total trading value in case of losing / number of losses". The loss loss rate is an example of an evaluation axis for evaluating, comparing, and diagnosing loss patterns and giving advice on how to make losses smaller than the current situation.

The trading profit / loss, which is an example of the evaluation axis, is an example of the evaluation axis showing the total profit / loss of the traded products in a predetermined period.
"Trading profit / loss =
Win rate x trading value when winning x winning profit rate / number of wins x principal x (number of elapsed days ÷ number of days of principal rotation) / trading value per transaction + (1-win rate) x trading value when losing x It is calculated by "Loss loss rate / Number of losses x Principal x (Elapsed days ÷ Number of days of rotation of principal) / Trading value per transaction".

Trading profit / loss is an evaluation axis of trading data including wins and losses, and is an example of an axis for evaluating where there is a problem in trading and what is good. Trading profit / loss is an example of an evaluation axis for extracting problems, evaluating, comparing, and diagnosing, and giving advice on how to further improve trading. The total profit / loss is calculated by "total profit / loss = trading profit / loss + unrealized profit / loss".

The rate of increase / decrease of owned stocks, which is an example of the evaluation axis, is an example of the evaluation axis calculated by "profit / loss amount of all stocks held / holding amount". The profit / loss amount of all the holdings is the total value of "(current price-buying price) x number of purchased shares" of the holdings. The holding amount is the total value of "buying price x number of shares purchased" of the holdings. The rate of increase / decrease in stocks held is an example of an evaluation axis that evaluates, compares, diagnoses, and analyzes data that is being bought and held that has not yet been sold. This is an example of an evaluation axis for giving advice on.

The principal increase / decrease rate, which is an example of the evaluation axis, is calculated by "total profit / loss / principal" and "(trading profit / loss + profit / loss amount of all stocks held) / principal / elapsed period (year)". The principal increase / decrease rate is an example of an evaluation axis for comprehensively evaluating, evaluating, comparing, diagnosing, and giving advice, including the trading status and the holding status.

(Details of diagnostic processing)
5 to 11 are flowcharts showing a diagnostic process of the advice generation unit 321 in the server 3 according to the present embodiment. FIG. 5 shows a diagnostic process based on the principal rotation period.

(Step S501)
The advice generation unit 321 determines whether or not the principal rotation period is within one week. When the principal rotation period is within one week (YES in step S501), the advice generation unit 321 executes the process of step S502. When the principal rotation period is longer than one week (NO in step S501), the advice generation unit 321 executes the process of step S503.

(Step S502)
The advice generation unit 321 describes the buying and selling tendency of the user as
-Information on the user's trading tendency-Information on the reason for the user's trading tendency-Information on the social aspect of the user's trading tendency-Generate a diagnostic result including information for improving the user's trading tendency (steps S504 and S506). , S507 as well).

As an example, the advice generation unit 321 performs the following evaluation, comparison, diagnosis, and advice on the evaluation axis of rotational force as a user's trading tendency. That is, "We are buying and selling frequently, which is close to day trading and scalping. Since the principal rotates once within a week, the stocks change frequently. There is a tendency to emphasize technical and win rates, and both wins and losses are bought and sold 1. The rate of return per trade usually tends to be low. It is important to look at other indicators such as the winning rate of return. As an improvement proposal, if the average trading period difference is negative or close to 0, you win. It is recommended to extend the average trading period of. "

(Step S503)
The advice generation unit 321 determines whether or not the principal rotation period is longer than one week and is within one month. When the principal rotation period is longer than one week and within one month (YES in step S503), the advice generation unit 321 executes the process of step S504. When the principal rotation period is longer than one month (NO in step S503), the advice generation unit 321 executes the process of step S505.

(Step S504)
As an example, the advice generation unit 321 states that the user's trading tendency is "Because it makes one revolution within one month, the stocks are replaced 10 times or more in one year. It is in the category of swing trading, but it is wide. Because of the concept, it is further subdivided according to the average trading period and the trading value per trading. However, in general, technically-oriented, material shareholders are used to buy and sell moving stocks. It becomes a style. In order to increase assets in this type, the difference between the winning rate, the winning profit rate and the losing loss rate is first important. Refer to the evaluation axes such as the winning profit rate, the losing loss rate, and the total profit rate. Make a comparison and diagnosis.

(Step S505)
The advice generation unit 321 determines whether or not the principal rotation period is longer than one month and is within six months. When the principal rotation period is longer than one week and within one month (YES in step S505), the advice generation unit 321 executes the process of step S506. When the principal rotation period is longer than 6 months (NO in step S505), the advice generation unit 321 executes the process of step S507.

(Step S506)
As an example, the advice generation unit 321 has a trading tendency of the user, "The trading frequency is such that the stocks are replaced several times a year. If "the average trading period in the case of winning-the average trading period in the case of losing" is a large plus, it can be said that there is a high possibility that asset formation has been completed. Naturally, it is determined by the balance with other evaluation axes, but with regard to the trading frequency, it can be done at a reasonable frequency, and it is a level that can respond to various changes. It is possible to respond not only to technical and fundamentals, but also to rapid changes in market trends and world conditions. In the case of this trading tendency, the most important thing is the difference between the winning rate of return and the losing loss rate, and the larger the difference, the better the operation. ] And make a diagnosis.

(Step S507)
As an example, the advice generation unit 321 states that the user's trading tendency is "when both the average holding period and the principal turnover period exceed half a year, the trading tendency changes greatly depending on the status of the stocks held. The case where the stocks held have unrealized losses. This is because there are many cases where there are a lot of bad debts. So-called stop-loss insurance is not possible, and only bad stocks are held, that is, it is in a salted state. I'm addicted to it, but the bad debts (bad assets) of households are the existence of salted stocks. The cause is likely to be caused by not buying and selling too much, and it is often included in this buying and selling tendency. Other evaluation axes Whether or not this case applies is determined by combining with. In particular, the important evaluation axis is the diagnosis of trading profit and loss and the analysis of holding status. As for trading advice, if the above is true, the stocks held While arranging even little by little, buy and sell and activate. "

FIG. 6 is a flowchart showing a diagnostic process based on the winning rate of return of the advice generation unit 321 in the server 3 according to the present embodiment.

(Step S601)
The advice generation unit 321 determines whether or not the winning rate of return is less than 5%. When the winning rate of return is less than 5% (YES in step S601), the advice generation unit 321 executes the process of step S602. When the winning rate of return is not less than 5%, that is, 5% or more (NO in step S601), the advice generation unit 321 executes the process of step S603.

(Step S602)
The advice generation unit 321 describes the buying and selling tendency of the user as
-Information on the user's trading tendency-Information on the reason for the user's trading tendency-Information on the social aspect of the user's trading tendency-Generate a diagnostic result including information for improving the user's trading tendency (steps S604, S606). , S608, S609 as well).

As an example, the advice generation unit 321 states that the user's trading tendency is "The winning rate of return is too low. Therefore, unless it is covered by the winning rate or the turning force, the assets will decrease. The winning profit is higher than the absolute value of the losing loss rate. If the rate is low, there is much room for improvement. If the average holding period when winning is less than a week, it may be a little too early. The selection of the stock to buy may be bad in the first place. Please refer to the index of trading analysis. "

(Step S603)
The advice generation unit 321 determines whether or not the winning rate of return is 5% or more and less than 10%. When the winning rate of return is 5% or more and less than 10% (YES in step S603), the advice generation unit 321 executes the process of step S604. When the winning rate of return is not less than 10%, that is, 10% or more (NO in step S603), the advice generation unit 321 executes the process of step S605.

(Step S604)
As an example, the advice generation unit 321 states that the user's trading tendency is "If the turnover rate is high, the losing loss rate is suppressed, and the winning rate is high, the assets may increase. If you do not meet the requirements, you tend to be in a situation where your assets do not increase despite your busy schedule. You may be good at buying and selling, but you may have difficulty selecting stocks. However, if it is difficult to obtain a large price range, it is necessary to reconfirm whether there are any mistakes in the stock selection in the first place. It is necessary to confirm whether there are any mistakes in the stock selection by trading profit / loss and trading pattern analysis. There is. ”And make a diagnosis.

(Step S605)
The advice generation unit 321 determines whether or not the winning rate of return is 10% or more and less than 20%. When the winning rate of return is 10% or more and less than 20% (YES in step S605), the advice generation unit 321 executes the process of step S606. When the winning rate of return is not less than 20%, that is, 20% or more (NO in step S605), the advice generation unit 321 executes the process of step S607.

(Step S606)
As an example, the advice generation unit 321 states that the user's trading tendency is "the winning rate of return is high and excellent. The winning rate is high and the losing loss rate is suppressed. If the turnover is effective, the assets will increase sufficiently. If possible, the pace of asset increase will increase by raising the rate of return to the next level. Is it possible to extend the average holding period when winning? Winning stocks based on trading profit / loss and trading pattern analysis I would like to think of a way to further increase the pace of increase by analyzing the above. By using strategic stocks, the possibility of getting a larger price range will increase. "

(Step S607)
The advice generation unit 321 determines whether or not the winning rate of return is 20% or more and less than 50%. When the winning rate of return is 20% or more and less than 50% (YES in step S607), the advice generation unit 321 executes the process of step S608. When the winning rate of return is not less than 50%, that is, 50% or more (NO in step S607), the advice generation unit 321 executes the process of step S607.

(Step S608)
As an example, the advice generation unit 321 states that the user's trading tendency is "It is sufficient if the price range is as large as this on average. How effective the rotation is, the loss loss rate, the winning rate, and the possession. It is important to note that there is no loss in the brand. If there are any drawbacks in the above points, there is still room for improvement. Of particular importance is the rotational force. If the rotational force is too low, it should be There is a great possibility that the pace of asset growth will increase even more. "

(Step S609)
As an example, the advice generation unit 321 stated that the user's buying and selling tendency was "If you look only at this number, you are getting enough profit. If the other numbers below are also excellent, the rhythm of increasing assets steadily. It has been acquired. There is no problem in terms of (1) how effective the turnover is, (2) what is the loss loss rate, (3) what is the win rate, and (4) whether there is any loss in the stocks held. It can be said that it is ideal. If there is a problem with any of the above four, improve from there. For example, there are many stocks that have large losses in their holdings, and profit taking is firm. On the other hand, it is not possible to cut losses and it remains, so it is important to learn how to deal with losses as soon as possible. Profit taking should be slow and loss cuts should be done early. " Make comparisons and diagnoses.

FIG. 7 is a flowchart showing a diagnostic process based on the losing loss rate of the advice generation unit 321 in the server 3 according to the present embodiment.

(Step S701)
The advice generation unit 321 determines whether or not the losing loss rate is larger than −5% and 0% or less. When the losing loss rate is larger than -5% and 0% or less (YES in step S701), the advice generation unit 321 executes the process of step S702. When the losing loss rate is not greater than -5%, that is, -5% or less (NO in step S701), the advice generation unit 321 executes the process of step S703.

(Step S702)
The advice generation unit 321 describes the buying and selling tendency of the user as
-Information on the user's trading tendency-Information on the reason for the user's trading tendency-Information on the social aspect of the user's trading tendency-Generate a diagnostic result including information for improving the user's trading tendency (steps S704, S705). The same applies).

As an example, the advice generation unit 321 states that the user's trading tendency is "The loss rate in the case of losing can be sufficiently controlled, and the result is excellent. If the winning rate and the winning profit rate are sufficient and there is no problem with the holding situation, it can be said that the rhythm is that assets will increase. However, the most important thing is how large the "winning rate of return + losing loss rate" is. If the winning rate of return is 5% and the losing loss rate is -5%, the difference is 0. If the winning percentage is 50%, there will be no loss or profit in buying and selling. It will be a busy sale. On the other hand, when the winning rate of return is 30% and the losing loss rate is -5%, the difference is 25%, which is sufficiently large. In this case, even if the winning percentage is 50%, the funds will increase sufficiently. It is necessary to combine it with other indicators, but it can be said that the losing loss rate is excellent. ] And make a diagnosis.

(Step S703)
The advice generation unit 321 determines whether or not the losing loss rate is greater than -10% and -5% or less. When the losing loss rate is larger than -10% and -5% or less (YES in step S703), the advice generation unit 321 executes the process of step S704. When the losing loss rate is not greater than -10%, that is, -10% or less (NO in step S703), the advice generation unit 321 executes the process of step S705.

(Step S704)
As an example, the advice generation unit 321 states that the user's trading tendency is "The loss rate is sufficiently suppressed, and risk management that does not deepen the damage is well done. There are stocks that have been deeply damaged. Unless otherwise, the loss cut works very well. In this case, it is most important that the winning rate is well above the losing loss rate. If both indicators are at similar levels, then the winning rate will gradually increase. If you are busy but your assets do not increase, you need to take profits slowly and stop loss early. You need to make sure that the first stock selection is correct by analyzing the trading pattern. There is. ”And make a diagnosis.

(Step S705)
As an example, the advice generation unit 321 stated that the user's buying and selling tendency was "The loss cut tends to be delayed and the damage is deepened. In order to make the rhythm of increasing assets, the loss cut should be done early and cleanly. It is very important to control the loss because if you have an asset of 1 million yen and you have a 20% loss, it will be 800,000 yen. Must generate as much as 25% profit. If profit is made, profit will be a virtuous cycle that calls for profit, but conversely, if a large loss is made and funds are reduced, the principal will be reduced. We have to do it with less and less money, and it will be difficult to emerge. If possible, we will try to keep the loss loss rate to 10% or less. "

FIG. 8 is a flowchart showing a diagnostic process based on trading profit / loss of the advice generation unit 321 in the server 3 according to the present embodiment.

(Step S801)
The advice generation unit 321 determines whether or not the trading profit / loss is larger than 0% and 10% or less. When the trading profit / loss is larger than 0% and 10% or less (YES in step S801), the advice generation unit 321 executes the process of step S802. When the trading profit / loss is 0% or less or larger than 10% (NO in step S801), the advice generation unit 321 executes the process of step S803.

(Step S802)
The advice generation unit 321 describes the buying and selling tendency of the user as
-Information on the user's trading tendency-Information on the reason for the user's trading tendency-Information on the social aspect of the user's trading tendency-Generate a diagnostic result including information for improving the user's trading tendency (steps S804, S806). , S808, S809 as well).

As an example, the advice generation unit 321 stated that the user's buying and selling tendency was "It is very important to have a style in which funds are steadily increasing in the current low interest rate era. It can be said that there is still room for improvement. "

(Step S803)
The advice generation unit 321 determines whether or not the trading profit / loss is larger than 10% and 20% or less. When the trading profit / loss is larger than 10% and 20% or less (YES in step S803), the advice generation unit 321 executes the process of step S804. When the trading profit / loss is 10% or less or larger than 20% (NO in step S803), the advice generation unit 321 executes the process of step S805.

(Step S804)
As an example, the advice generation unit 321 states that the user's buying and selling tendency is "excellent because the annual rate of return is greater than 10%, which is excellent. However, if desired, the compound interest effect is included and 10%. Since it is a platform, you can aim for a higher level. As for the improvement point, it is important to look at other indicators and improve the bad points. If the winning profit rate is bad, it is the improvement and the turnover rate is bad. For example, increase the rotation a little. "

(Step S805)
The advice generation unit 321 determines whether or not the trading profit / loss is larger than 20%. When the trading profit / loss is larger than 20% (YES in step S805), the advice generation unit 321 executes the process of step S806. When the trading profit / loss is not larger than 20%, that is, when it is 20% or less (NO in step S805), the advice generation unit 321 executes the process of step S807.

(Step S806)
As an example, the advice generation unit 321 stated that the user's trading tendency was "The principal has increased more than 20% per annum, and the assets have been sufficiently formed. After that, the bad index is improved and the good index is used. By making it even better, we can aim for even higher levels. We are doing well with regard to trading stocks, but if the stocks we own also have a lot of valuation gains, it can be said that it is truly ideal. " Make a diagnosis.

(Step S807)
The advice generation unit 321 determines whether or not the trading profit / loss is larger than -10% and 0% or less. When the trading profit / loss is larger than -10% and 0% or less (YES in step S807), the advice generation unit 321 executes the process of step S808. When the trading profit / loss is −10% or less (NO in step S807), the advice generation unit 321 executes the process of step S809.

(Step S808)
As an example, the advice generation unit 321 states that the user's buying and selling tendency is "The buying and selling is in the minus zone, and even if the buying and selling is hard, the result is not followed, which is an uninteresting result. This is especially true if you have problems with your stocks. It is important to first look for improvement points where to improve. Whether there is a problem with trading or a problem with stock selection can be found by trading pattern analysis. Depending on which trading pattern is most common, you can see whether there are more problems with trading or stock selection. If there is a problem with buying and selling, calculate the "winning rate of return + losing loss rate". If the "winning rate of return + losing loss rate" is close to 0 or negative, this value will be improved (increasing the plus) by slowly taking profits and cutting losses early. Is important. And let's move up to the plus zone by increasing the winning percentage. Try to follow the advice. ] And make a diagnosis.

(Step S809)
As an example, the advice generation unit 321 states that the user's trading tendency is "It has decreased by more than 10% a year, and the assets are shrinking. Unless the situation of the stocks held is good, It can be said that there is a lot of room for improvement in buying and selling, and it is necessary to fix various points. Where should I fix it? It is important to understand. If there is a problem with stock selection, it is important to change that point first. Try buying and selling with strategic stocks. If there is a problem with buying and selling, loss cut There may be problems such as slow profit settlement, poor win rate, and too slow turnover. Look at your own performance on each evaluation axis and fix it from where there is a lot of room for improvement. As mentioned above, I think there is a high possibility that it will be improved by following the advice. "

FIG. 9 is a flowchart showing a trading pattern classification process of the advice generation unit 321 in the server 3 according to the present embodiment. In the following processing, it is explained that the judgment is made using the current price, but the market price after the sale (including the market price three months after the sale and the current price) is used without being limited to the current price. It may be determined.

(Step S901)
The advice generation unit 321 determines whether or not the bid price is smaller than the ask price. If the bid price is smaller than the ask price (YES in step S901), the process of step S902 is executed. When the bid price is not smaller than the sell price, that is, when the bid price is equal to or greater than the sell price (NO in step S901), the process of step S907 is executed.

(Step S902)
The advice generation unit 321 determines whether or not the selling price is smaller than the current price. If the selling price is smaller than the current price (YES in step S902), the process of step S903 is executed. When the selling price is not smaller than the current price, that is, when the selling price is equal to or greater than the current price (NO in step S902), the process of step S904 is executed.

(Step S903)
The advice generation unit 321 describes the buying and selling tendency of the user as
-Information on the user's trading tendency-Information on the reason for the user's trading tendency-Information on the social aspect of the user's trading tendency-Generate a diagnostic result including information for improving the user's trading tendency (steps S905 and S906). , S908, S810, S911 as well).

As an example, the advice generation unit 321 describes the user's trading tendency (winning pattern 1 [buying price <selling price <current price]) as "a user with many trading patterns may still be able to increase profits. It's not wrong, and after that, we need to see if we can get a bigger price range or if profits are taken too early, and if it's too late, we may have missed another chance. The surface of revolution is also important. "

Furthermore, the advice generation unit 321 responded to the winning pattern 1, saying, "In the future, we can make further improvements depending on how to manage trading from the stock selection stage and how to replace stocks." Generate advice.

(Step S904)
The advice generation unit 321 determines whether or not the current price is larger than the bid price. If the current price is larger than the bid price (YES in step S904), the process of step S905 is executed. When the current price is not larger than the bid price, that is, the current price is equal to or less than the bid price (NO in step S904), the process of step S906 is executed.

(Step S905)
As an example, the advice generation unit 321 describes the user's trading tendency (winning pattern 2 [buying price <selling price and selling price ≥ current price, and current price> buying price]) as "a user with many trading patterns selects a brand. Is doing well and buying and selling well. However, if you want, it is important to buy and sell with a stock that can take a larger price range. Especially in the case where the winning profit margin is low. Even more so. Because we buy and sell stocks that do not have a large price range, the winning profit margin does not increase. "

Further, the advice generation unit 321 "improves when switching to the buying and selling of strategic stocks according to the winning pattern 2. In this case, by improving the winning rate of return, which is the most important index. There is. "

(Step S906)
As an example, the advice generation unit 321 describes the user's trading tendency (winning pattern 3 [buying price <selling price, selling price ≥ current price, and current price ≤ buying price]) as "a user with many trading patterns is in the first place. The stock selection was wrong, and I bought a stock that I shouldn't buy at that time, and I won because I sold it quickly. The buying and selling went well, but the stock selection was wrong. If so, there is a high possibility that the stocks that are currently in motion, such as material stocks and maker stocks, are fascinated by the stocks that are not profitable unless they are bought and sold. It means that you have to buy and sell. Therefore, you have to buy and sell. "

Further, the advice generation unit 321 responds to the winning pattern 3, "It is important to select a stock that is safe to hold and that is safe to hold, not a stock that cannot be held with confidence. Then, it is more important to buy and sell. I can afford it. "

(Step S907)
The advice generation unit 321 determines whether or not the selling price is larger than the current price. If the selling price is larger than the current price (YES in step S907), the process of step S908 is executed. When the selling price is not larger than the current price, that is, when the selling price is equal to or less than the current price (NO in step S907), the process of step S909 is executed.

(Step S908)
As an example, the advice generation unit 321 describes the user's trading tendency (losing pattern 1 [buy ≥ selling price> current price]) as "a user with many trading patterns has a problem in stock selection. Now, only popular stocks are used. If you make a move on the stock, or if you make a move on the stock that has the material, you will lose such a loss. The essence of such a stock is a stock that you should not own, a stock that you will lose a lot if you do not sell it There is. ”And make a diagnosis.

Further, the advice generation unit 321 "needs to change the stock selection considerably when there are many losing patterns 1 and winning patterns 3" according to the losing pattern 1. Change from a go-to style to an investment style. Since there is a high possibility that trading is a skillful person, if stock selection is done properly, there is a possibility that the results will increase dramatically. First, strategy. Try buying and selling by brand. "

(Step S909)
The advice generation unit 321 determines whether or not the current price is larger than the bid price. If the current price is larger than the bid price (YES in step S909), the process of step S910 is executed. When the current price is not larger than the bid price, that is, the current price is equal to or less than the bid price (NO in step S909), the process of step S911 is executed.

(Step S910)
As an example, the advice generation unit 321 describes the user's trading tendency (loss pattern 2 [buying price ≥ selling price, and selling price ≤ current price, and current price> buying price]) as "a user with many trading patterns selects a brand. That's fine, but the loss cut is too early, and the criteria for judging whether to close or not are ambiguous. It is necessary to try other indicators as well. If there are many winning patterns 1, stock selection Can be said to be very excellent. "

Further, the advice generation unit 321 responds to the losing pattern 2, "The more skillful the buying and selling, the more the assets will increase. The winning rate of return, the losing loss rate, the difference, etc. are important indicators." And generate advice.

(Step S911)
As an example, the advice generation unit 321 describes the user's trading tendency (losing pattern 3 [buying price ≥ current price ≥ selling price]) as "a user with many trading patterns has room for improvement in both stock selection and trading. In the trading pattern, the loss is kept small, and if the win is large, there is a possibility that the ideal way of winning is achieved. "

Further, the advice generation unit 321 generates advice according to the losing pattern 3, "If you lose a lot, it is important to correct the mistake in stock selection."

FIG. 10 is a flowchart showing a diagnostic process based on the rate of increase / decrease of owned stocks (hereinafter, simply referred to as “rate of increase / decrease”) of the advice generation unit 321 in the server 3 according to the present embodiment.

The advice generation unit 321 classifies the trading data into the holding stock data and the trading data, and calculates the rate of increase / decrease of the holding stock with reference to the holding stock data. Then, the advice generation unit 321 executes the following diagnostic processing.

(Step S1001)
The advice generation unit 321 determines whether or not the rate of increase / decrease is greater than -10% and 0% or less. When the rate of increase / decrease is larger than -10% and 0% or less (YES in step S1001), the advice generation unit 321 executes the process of step S1002. When the rate of increase / decrease is -10% or less or greater than 0% (NO in step S1001), the advice generation unit 321 executes the process of step S1003.

(Step S1002)
The advice generation unit 321 describes the buying and selling tendency of the user as
-Information on the user's trading tendency-Information on the reason for the user's trading tendency-Information on the social aspect of the user's trading tendency-Generate a diagnostic comparison result including information for improving the user's trading tendency (step S1004, The same applies to S1006 and S1007).

As an example, the advice generation unit 321 states that the user's trading tendency is "Some stocks are profitable and some stocks are losing money. In addition, the evaluation differs greatly depending on the trading profit and loss. If it is big positive, there seems to be few problems. If the trading profit / loss is a little, or if it is negative, there seems to be a lot of room for improvement. It is important for you to do this. By improving trading and stock selection, the stocks you own should also improve. I think there is a long way to go, but there is a lot of room for improvement, and factors that will change. It can be said that there are many. "

(Step S1003)
The advice generation unit 321 determines whether or not the rate of increase / decrease is -10% or less. When the rate of increase / decrease is −10% or less (YES in step S1003), the advice generation unit 321 executes the process of step S1004. When the rate of increase / decrease is not -10% or less (NO in step S1003), the advice generation unit 321 executes the process of step S1005.

(Step S1004)
As an example, the advice generation unit 321 stated that the user's trading tendency was "Salted stocks have appeared, and there seems to be a lot of room for improvement unless the trading profit and loss is very good. It is necessary to start with improvement. It is highly possible that the remaining stocks are the stocks that are held because they cannot be bought or sold, the loss cannot be cut off, and the stocks that have failed should be cut off early. It's very important in some cases. Don't drag forever. It's easy to say, but it's certainly difficult to cut losses. If you're not good at it, try to imitate the support content first. This is because it opens up possibilities. It is important to sort out the stocks held little by little and change to a state with unrealized gains. "

(Step S1005)
The advice generation unit 321 determines whether or not the rate of increase / decrease is larger than 0% and smaller than 10%. When the rate of increase / decrease is larger than 0% and smaller than 10% (YES in step S1005), the advice generation unit 321 executes the process of step S1006. When the rate of increase / decrease is 10% or more (NO in step S1005), the advice generation unit 321 executes the process of step S1007.

(Step S1006)
As an example, the advice generation unit 321 describes the user's trading tendency as "If there is no problem in trading profit and loss, it can be said that it is going well. However, it is important to see it together with the trading pattern analysis. In the trading pattern classification process. If there are many winning patterns 2 and 3 instead of winning pattern 1, it is necessary to review the stock selection because it is highly likely that you are buying a stock that does not have a large price range. A strategy that can take a larger price range. Try to use more brands. "

(Step S1007)
As an example, the advice generation unit 321 describes the user's trading tendency as "If the trading profit / loss is also positive, there seems to be few problems. However, other evaluation axes such as turning power, winning rate of return, losing loss rate, winning rate, etc. It is necessary to look at it together. We will improve the weak points. "

FIG. 11 is a flowchart showing a ranking process based on the principal increase / decrease rate of the advice generation unit 321 in the server 3 according to the present embodiment. The advice generation unit 321 may perform comparison processing and ranking processing using evaluation indexes other than the principal increase / decrease rate, or may perform comparison processing and ranking processing using a plurality of evaluation indexes. ..

(Step S1101)
The advice generation unit 321 determines whether or not the principal increase / decrease rate is larger than 30%. When the principal increase / decrease rate is larger than 30% (YES in step S1101), the advice generation unit 321 executes the process of step S1102. When the principal increase / decrease rate is not larger than 30% (NO in step S1101), the advice generation unit 321 executes the process of step S1103.

(Step S1102)
The advice generation unit 321 describes the buying and selling tendency of the user as
-Information on the user's trading tendency-Generate a diagnostic result including information for improving the user's trading tendency (the same applies to steps S1104, S1106, S1108, and S1109).

As an example, the advice generation unit 321 describes the user's trading tendency (rank special A) as "It is ideal because assets are increasing at a pace higher than the market average. Either the trading profit or loss and the valuation gain are weighted. It depends on whether it is high or not, but if it is a trading profit and loss entity, the turnover will also work well. "

Further, the advice generation unit 321 generates an advice according to the rank special A, "By improving the weak points in each evaluation axis, the profitability is further improved and the pace of asset increase is likely to increase."

(Step S1103)
The advice generation unit 321 determines whether or not the principal increase / decrease rate is larger than 10% and 30% or less. When the principal increase / decrease rate is larger than 10% and 30% or less (YES in step S1103), the advice generation unit 321 executes the process of step S1104. When the principal increase / decrease rate is 10% or less (NO in step S1103), the advice generation unit 321 executes the process of step S1105.

(Step S1104)
As an example, the advice generation unit 321 describes the user's trading tendency (rank A) as "around the year, even if it is not so, the funds are increasing year by year, and profits are calling for profits. It is in operation. There are irregularities depending on the year, but the pace is higher than the average. "

In addition, the advice generator 321 responds to Rank A, "Check the index of how it compares to the Nikkei average, and see your own growth rate compared to the market average. If it is below the market average, there is room for improvement. There is still more. Even if it exceeds the limit, we should recognize the weak points and improve them. "

(Step S1105)
The advice generation unit 321 determines whether or not the principal increase / decrease rate is larger than 0% and 10% or less. When the principal increase / decrease rate is larger than 0% and 10% or less (YES in step S1105), the advice generation unit 321 executes the process of step S1106. When the principal increase / decrease rate is 0% or less (NO in step S1105), the advice generation unit 321 executes the process of step S1107.

(Step S1106)
As an example, the advice generation unit 321 states that the user's trading tendency (rank B) is "the negative range is small, but the principal is broken, and there is room for improvement in various ways. First, there is a loss in the stocks held. Let's check in the order of whether it is out or whether there is a loss in buying and selling. "

Furthermore, the advice generation unit 321 responded to Rank B, saying, "If there is a loss in the stocks you own, the point that you should not make a loss cut is the first point to be corrected. The selection of the first stock to buy is appropriate. Whether or not it is also a point. "

(Step S1107)
The advice generation unit 321 determines whether or not the principal increase / decrease rate is larger than -10% and 0% or less. When the principal increase / decrease rate is larger than -10% and 0% or less (YES in step S1107), the advice generation unit 321 executes the process of step S1108. When the principal increase / decrease rate is −10% or less (NO in step S1107), the advice generation unit 321 executes the process of step S1109.

(Step S1108)
As an example, the advice generation unit 321 describes the user's trading tendency (rank C) as "the loss is swelling, and it is recommended that it be improved immediately. First, grasp the problem. Loss on the stocks held. If there is a loss, check if there is a loss on the traded stock. If there is a loss on the traded stock, refer to the winning rate, losing loss rate, trading pattern analysis, etc. " Compare with and make a diagnosis.

Furthermore, the advice generation unit 321 gives advice according to rank C, "It should be improved from a particularly bad place. Please refer to the advice on how to improve from a bad evaluation axis." Generate.

(Step S1109)
As an example, the advice generation unit 321 describes the user's trading tendency (rank D) as "The assets are decreasing year by year. First of all, the problem is whether there is a problem with the trading profit or loss or the rate of increase / decrease of the stocks held. It is important to recognize. "

Furthermore, the advice generation unit 321 responded to Rank D by saying, "The loss cannot be cut, and the unrealized loss of the stocks held has not expanded, or the turnover is too fast, and the assets do not increase at all despite being busy. In the former case, the loss rate and 6-pattern trading analysis are important. In the latter case, the winning rate of return, comprehensive loss analysis, and turnover index are important. " Generate.

(Decomposition formula of trading profit and loss)
The decomposition formula of trading profit and loss is shown below.

Trading profit / loss =
Win rate x trading value when winning x winning profit rate / number of wins x principal x (number of elapsed days ÷ number of days of principal rotation) / trading value per transaction + (1-win rate) x trading value when losing x Loss loss rate / Number of losses x Principal x (Elapsed days ÷ Number of days of rotation of principal) / Trading price per transaction The following is a decomposition formula of trading profit and loss, including numerical examples when the principal is 5 million yen. show. Numerical examples are shown in parentheses in [].

Trading profit / loss =
Win rate [0.33] x Trading value when winning [29.7 million yen] x Winning rate of return [0.41] / Number of wins x Principal [5 million yen] x (Elapsed days [1224] / Rotation of principal Number of days [53]) / Trading price per transaction [670,000 yen]
+ (1-Win rate) x Trading value when losing [77.73 million yen] x Losing loss rate [-0.08] / Number of losses x Principal [5 million yen] x (Elapsed days [1224] ÷ Principal Number of rotation days [53]) / Trading price per transaction [670,000 yen]
The advice generation unit 321 of the server 3 generates a decomposition formula of trading profit / loss including numerical values as a diagnosis result regarding the trading data of the user. Further, the advice generation unit 321 generates advice including at least the winning rate, the winning rate of return, the losing loss rate, and the evaluation index including the number of days of principal turnover (principal turnover period) included in the above decomposition formula. ..

[Example of advice]
An example of the advice according to this embodiment is shown below. The advice generation unit 321 of the server 3 generates each advice. The control unit 22 of the terminal 2 causes the display unit 23 to display each advice. The content of the advice shown below is an example and does not limit the present invention.

(First example of advice)
"The turnover period of the principal is 3 days, and we are good at buying and selling with a very effective turnover rate. For the principal of 1 million yen, 100 turns in one year, and the trading value of 100 million yen Because the rotation is too fast, the rate of return per transaction is inevitably low.

Especially the winning rate of return of 5% may be too low.

The winning rate is 60%, the winning rate of return is 5%, and the losing loss rate is -8%. Although the winning percentage is high, the loss loss is large and the loss cut tends to be delayed, so it can be said that there is an urgent need to improve the loss loss rate. "
(Second example of advice)
"It seems that you don't like buying and selling. For the past year, if you buy it, you've been holding it and you haven't bought or sold it. I think you are.

For the principal of 10 million yen, the trading value is 5 million yen and the cash is 5 million yen. The winning rate of the stocks held is 80%, and the rate of return if won is 1.2 times high, which is sufficiently high. It seems that the investment stance is to carefully select good stocks and purchase them little by little at the right timing. The loss rate of losing stocks is also kept low at around -10%. It is a stance of carefully selecting and investing in stocks. It can be said that it is a work that can be done only by those who have financial power.

However, there are various big opportunities in the stock market. Not buying or selling or replacing stocks means that you are likely to miss the opportunity. By increasing the trading value, you can get many times more profit opportunities than the principal. With a principal of 10 million yen, you can dramatically increase profit opportunities by replacing stocks once every three months. If you do it once a week, you will be too busy, but if you do it once every three months, it will take almost no effort. Being able to refresh once every three months makes it easier to incorporate brands that match the times, and let's respond flexibly to changes.

Since stocks are constantly changing, it can be said that it is indispensable even for those who have abundant funds for buying and selling and stock replacement to respond to changes. However, the brands you should buy differ from time to time, and it is not easy to respond to changes. We support that area in trading support. "
(Third example of advice)
"The turnover period of the principal is one year. In other words, with a principal of 1 million yen, we only buy once a year, we do not buy or sell, we continue to hold 1 million yen. The trading value is zero, but the winning rate of the stocks owned is 20%, the losing loss rate is -30%. It is in a state of being unable to move with a loss. The wound is deepened by not cutting the loss.

First of all, it is recommended to move even a part and try buying and selling. By revitalizing the funds you have moved, you will be able to generate profits, which will motivate you to revitalize other salted stocks, and let's gradually move toward improvement. The most important thing to keep in mind when moving is to cut losses early and take profits slowly. Stop-loss insurance will be difficult until you get used to it, so we recommend that you follow the trading support. "
(4th example of advice)
"The rotation period of the principal is 2 months, and the rotation is moderate. It is the trading value of 6 million yen for 6 rotations in one year for the principal of 1 million yen. The winning rate is 40%, the winning rate of return is 40%, and the losing rate of return is -8%.

Although the winning rate is low, the winning rate of return is extremely high at 1.4 times, and on the contrary, the loss cut in case of losing is suppressed to -8%, so the assets are steadily increasing and ideal trading. Let's say. The frequency of rotation is about once every two months, and the brands are replaced, so I am not busy.

If you win, the holding period exceeds 3 months on average, and if you lose, the trading period is 2 weeks. We buy and sell for asset formation. 』\
(5th example of advice)
"The turnover period of the principal is one month, and the moderate turnover is effective. For the principal of 1 million yen, 12 turns in one year and the trading value of 12 million yen. The winning rate is 70%, winning. The rate of return is 5% and the loss rate is -15%. We are conscious of the winning rate and have a high winning rate, but the winning rate is too low, the losing loss rate is too large, and the assets are decreasing. If you win, the holding period is too short and you tend to settle profits immediately, but on the other hand, for stocks that have lost, you have prolonged holding and the loss has expanded.

There is a tendency for loss cuts to be delayed, and it can be said that there is an urgent need to improve the loss loss rate. "
[Specific examples of basic numerical values (basic data) and evaluation indicators]
The advice generation unit 321 calculates an evaluation index from basic numerical values. The calculation of the evaluation index changes according to the level of profit and loss (level of detail). As the evaluation index changes, evaluation can be performed step by step, and comparison, diagnosis, and advice can be performed step by step. Specific examples of the differences in evaluation indexes according to the level are shown below. The following is a specific example, and does not limit the present invention.

(Specific example regarding the evaluation of total profit and loss)
The advice generation unit 321 calculates the principal increase / decrease rate by "principal increase / decrease rate = total profit / loss ÷ principal" and evaluates the total profit / loss.

The basic numbers are
·principal,
・ Total profit / loss, purchase price, sale price, number of purchases, current evaluation value, elapsed days, average holding days, benchmark (Nikkei average, etc.) increase / decrease rate during the elapsed period.

The evaluation index includes a rotational force index and a comprehensive index.

The rotational force index is
・ Number of rotations (= purchase price ÷ principal)
・ Number of rotation days (= number of elapsed days ÷ number of rotations)
・ There is an average number of days held.

The comprehensive index is
・ Principal profit / loss ratio (= total profit / loss ÷ principal)
・ Average purchase price ・ Average profit / loss (= total profit / loss ÷ number of purchases)
・ Principal profit / loss ratio (= purchase price ÷ principal x total profit / loss ÷ number of purchases ÷ purchase price ÷ number of purchases)
・ Principal profit / loss ratio (= number of revolutions x average profit / loss per transaction / purchase price per transaction)
・ There are comparison with the Nikkei average, cash ratio, investment ratio, current investment amount, etc.

(Specific example regarding evaluation of total trading profit and loss)
The advice generation unit 321 calculates the principal increase / decrease rate by "principal increase / decrease rate = (total trading profit / loss + total unrealized profit / loss) / principal" and evaluates the total trading profit / loss.

The basic numbers are
・ Principal ・ Total trading profit / loss ・ Purchase price ・ Number of wins ・ Total profit in case of winning ・ Total purchase price of winning ・ Total selling price of winning ・ Number of losses ・ Total purchase price of losing ・ Total selling price of losing ・In case of losing, there are total loss, number of trades, sale price, elapsed days, average trading period, etc.

The evaluation index is
・ Rotational power ・ Number of rotations of trading brand (= purchase price ÷ principal)
・ Number of days of trading issues (= number of elapsed days ÷ number of rotations)
・ Average number of days held of trading stocks ・ Principal profit / loss ratio (= total trading profit / loss ÷ principal)
・ Win rate of trading stocks (= number of wins ÷ number of trades)
・ Profit of winning each trading issue (= profit in case of winning ÷ number of wins)
・ Profit margin in case of winning of trading stock (= profit in case of winning ÷ winning trading value)
・ Loss per trading issue (= loss in case of losing ÷ number of losses)
・ Loss rate in case of losing trading stock (= loss in case of losing ÷ losing trading value)
And so on.

For example, trading profit and loss can be divided into the following factors. By this decomposition, it becomes possible to grasp the nature of buying and selling.

Total trading profit / loss = win rate (33%) x trading value when winning (29.7 million yen) x rate of return when winning (0.41) ÷ number of wins + (1-win rate) x trading value when losing (1-win rate) 77.73 million yen) x rate of return in case of losing (-0.08) ÷ number of losses x principal (5 million yen) x (elapsed days (1224) ÷ number of days of principal turnover (53)) / per transaction Trading price (670,000 yen)
The trading profit / loss is determined by the turning power, the profit rate in the case of winning, the loss rate in the case of losing, the principal, the winning rate, and the like. By separating the factors, it is possible to evaluate which factor is strong or weak, and the tendency of buying and selling becomes clear.

For example, unrealized gains and losses can be divided into the following factors.

Unrealized profit / loss = win rate (33%) x trading value when winning (29.7 million yen) x rate of return when winning (0.41) ÷ number of wins + (1-win rate) x trading value when losing (7773) (10,000 yen) x rate of return when losing (-0.08)) ÷ number of losses x principal (5 million yen) x (elapsed days (1224) ÷ number of days of principal turnover (53)) / per transaction Trading price (670,000 yen)
Regarding the evaluation of unrealized gains and losses, the turning power, the profit margin in the case of winning, the loss ratio in the case of losing, the principal, the winning percentage, etc. are important.

(Specific example regarding evaluation of total winning profit)
The advice generation unit 321 calculates the principal increase / decrease rate by "principal increase / decrease rate = (total winning profit + total losing loss + total unrealized profit / loss) / principal", and evaluates the total winning profit.

The basic numbers are
・ Principal, total profit, purchase price, sale price, elapsed days, average trading days, etc.

The evaluation index is
・ Rotational force / number of rotations = (purchase price ÷ principal)
・ Number of rotation days (= number of elapsed days ÷ number of rotations)
・ Average number of days held ・ Profit margin of winning (= total profit of winning ÷ purchase price of winning)
・ Win rate (= number of wins ÷ number of trades)
・ Profit per win (= profit in case of win ÷ number of wins)
・ Profit margin in case of winning (= profit in case of winning ÷ winning trading value)
・ Total profit of winning ・ Purchase price per win (= purchase price of winning ÷ number of wins)
And so on.

For example, winning profit can be divided into the following factors.

Winning profit = (win rate (= number of wins ÷ number of trades) (33%) x trading value when winning (29.7 million yen) x rate of return when winning (= (profit of winning pattern 1 + profit of winning pattern 2) + Profit of winning pattern 3) ÷ Trading value (0.41)) ÷ Number of wins) × (Principal (5 million yen) × (Elapsed days (1224) ÷ Number of days of principal rotation (53)) ÷ Each time Trading price (670,000 yen))
Winning profit = Profit of winning pattern 1 + Profit of winning pattern 2 + Profit of winning pattern 3 Winning profit = Profit that would have been obtained in winning pattern 1-Lost profit after selling winning pattern 1 + Selling winning pattern 2 Loss escaped in + Profit that would have been obtained by holding Win Pattern 2 + Win Pattern 3 (Current Valuation-Purchase Amount) -Win Pattern 3 (Loss if you continue to hold) -Win Pattern 3 Loss that could be avoided by buying and selling at (current valuation amount-sale amount) (specific example of valuation of winning profit pattern)
The advice generation unit 321 sets the principal increase / decrease rate as "principal increase / decrease rate = (total unrealized profit / loss + total profit of winning profit pattern 1 + total profit of winning profit pattern 2 + total profit of winning profit pattern 3 + losing loss pattern). Calculated by "total loss of 1 + total loss of losing loss pattern 2 + total loss of losing loss pattern 3) / principal", and the total winning profit is evaluated.

The basic number of winning pattern 1 is
·principal,
・ Total profit ・ Purchase price ・ Sale price ・ Elapsed days ・ Average number of trading days ・ Total profit and loss after trading ・ Total profit and loss in case of holding ・ Total trading profit and loss, etc.

The evaluation index of winning pattern 1 is
・ Average holding period, total profit obtained if not sold ・ Profit amount obtained if not sold per time ・ Profit obtained if not sold ÷ Profit of winning pattern 1 ・Total profit originally obtained ・ Total profit obtained ÷ Profit of winning pattern 1 ・ Average holding period ・ Period elapsed when not sold ・ Holding period when not sold after purchase,
・ Total profit obtained originally ÷ Holding period if not sold after purchase ・ Profit obtained if not sold ÷ Period elapsed if not sold, etc.

For example, the profit of the winning pattern 1 can be divided into the following factors.

Profit of winning pattern 1 = rate of winning pattern 1 (= (number of winning patterns 1 ÷ number of winnings) x (number of winnings ÷ number of trading)) x trading value in the case of winning pattern 1 (10,000 yen) x winning pattern 1 Rate of return (= profit of winning pattern 1 ÷ trading value of winning pattern 1) ÷ number of times of winning pattern 1 × principal (5 million yen) × number of elapsed days (1224) ÷ number of days of rotation of principal (= (number of elapsed days) ÷ (Trading price ÷ Principal)) (53) ÷ Trading price per transaction (670,000 yen))
Profit of winning pattern 1 = Profit that would have been obtained in winning pattern 1-Lost profit after sale of winning pattern 1 Profit margin of winning pattern 1 = (Profit that would have been obtained in winning pattern 1-Winning pattern 1 Lost profit after sale) ÷ Profit of winning pattern 1 = Profit of winning pattern 1 = Rate of winning pattern 1 (= Number of winning patterns 1 ÷ Number of trading) × Trading value in case of winning pattern 1 (10,000 yen) × (Profit that would have been obtained in winning pattern 1-lost profit after selling winning pattern 1) ÷ trading value of winning pattern 1 ÷ number of times of winning pattern 1 (total profit / loss)
In the server 3, the advice generation unit 321 acquires the trading data of the investment product, acquires the basic numerical value (basic data) from the acquired trading data, and calculates the evaluation index regarding the trading profit / loss and the unrealized profit / loss from the acquired basic numerical value. , The evaluation index related to the total profit and loss is acquired from the calculated evaluation index, and the information indicating the acquired evaluation index is generated.

FIG. 12 is a flowchart showing the processing of the total profit / loss analysis according to the present embodiment. FIG. 13 is a diagram showing an example of evaluation values of total profit / loss, trading profit / loss, and unrealized profit / loss according to the degree of detail according to the present embodiment.

As shown in FIG. 13, the total profit / loss is represented by the total of trading profit / loss and unrealized profit / loss. The unrealized gain / loss has the trading profit / loss as a parameter of the calculation formula, and is linked to the increase / decrease in the trading profit / loss. According to this, there is a possibility that the unrealized profit / loss will increase in accordance with the increase in the trading profit / loss, and the possibility that the total profit / loss will further increase will increase. That is, it is possible to expect a compound interest effect of the total profit / loss due to the synergistic effect of the trading profit / loss and the unrealized profit / loss.

In other words, the total profit / loss can be said to be the sum of the unrealized profit / loss obtained from the investment product and the profit / loss including the realized profit / loss.

The evaluation index of total profit and loss is
・ Turnover power ・ Winning rate of return (trading profit rate and unrealized rate of return)
・ Losing loss rate (trading loss rate and unrealized loss rate)
・ Cash ratio ・ Purchase win weight (win rate of unrealized trading)
・ Win rate (win rate of buying and selling)
And so on.

The total profit / loss is affected by various evaluation indexes depending on the level of detail of the evaluation numerical values, and various evaluation indexes according to the level of detail are evaluated. For example, when a calculation formula having a level of detail of 5 is used, the most subdivided evaluation index is used, so that more detailed analysis and evaluation are possible.

As shown in FIG. 12, in the server 3, the advice generation unit 321 as a diagnostic procedure analyzes the total profit and loss to grasp the outline of what is good and what is bad, and then deeply digs into the bad points to improve. Clarify what should be done.

(Step S1201)
The advice generation unit 321 determines whether or not there is a problem in the trading profit / loss among the total profit / loss. When there is a problem in trading profit / loss (Yes in step S1201), the advice generation unit 321 executes the determination in step S1202. When there is no problem in the trading profit / loss (that is, there is a problem in the unrealized profit / loss) (No in step S1201), the advice generation unit 321 executes the determination in step S1205.

(Step S1202)
The advice generation unit 321 determines whether or not there is a problem in the winning profit rate (trading profit rate). When there is a problem with the winning profit margin (Yes in step S1202), the advice generation unit 321 executes the process of step S1203. When there is no problem in the winning profit rate (that is, there is a problem in the losing loss rate) (No in step S1202), the advice generation unit 321 executes the process of step S1204.

(Step S1203)
The advice generation unit 321 analyzes the winning profit rate (trading profit rate).

(Step S1204)
The advice generation unit 321 analyzes the losing loss rate (trading loss rate).

(Step S1205)
The advice generation unit 321 determines whether or not there is a problem in the winning profit rate (unrealized profit rate). When there is a problem with the winning profit margin (Yes in step S1205), the advice generation unit 321 executes the process of step S1206. When there is no problem in the winning profit rate (that is, there is a problem in the losing loss rate) (No in step S1205), the advice generation unit 321 executes the process of step S1207.

(Step S1206)
The advice generation unit 321 analyzes the winning profit rate (unrealized profit rate).

(Step S1207)
The advice generation unit 321 analyzes the losing loss rate (unrealized loss rate).

As a specific example of steps S1205 to S1207, for example, the absolute value of the winning rate of return (unrealized rate of return) is larger than the threshold value A, and the absolute value of the losing loss rate (unrealized loss rate) is the threshold value B (<threshold value A). ), The advice generator 321 diagnoses that the winning profit rate is sufficiently large and the losing loss rate is sufficiently small, and sells the stock that has a small losing loss rate to cut the loss. You may generate advice that encourages you to buy investment products that are more profitable at the price you realize and sell. Because the winning profit is large, it makes sense to realize the loss early within the profit margin. However, if the length of the holding period (for example, days, months, etc.) of a stock with a small loss loss rate is shorter than a predetermined value, the advice generation unit 321 generates the above diagnosis and advice. do not do. This is because the holding period is still short, so there is a possibility that the operational results of the relevant issue have not been obtained.

In the analysis of steps S1203, S1204, S1206, and S1207, it is attempted to analyze whether the winning profit rate or the losing profit rate is larger (outperforming) than the comparison target (for example, the Nikkei average). May be good.

According to the above, for example, "Starting from the diagnosis of total profit and loss, the turning power is high, but the winning profit margin is low and the trading profit is low, so the compound profit effect is not effective, the unrealized loss is large, and the total profit and loss is also negative. Or, "The loss cut cannot be made, and the lost stock prolongs the holding, and the unrealized loss expands. ) Is high. "

Investment products are investment target products including Fx, stocks, investment trusts, ETFs, etc., and refer to variable products whose value fluctuates. However, it is not a strict unique calculation formula, and for example, the trading value per transaction can be replaced with (trading price ÷ number of trading).

The unrealized profit / loss is expressed by a function such as a cash ratio, a trading profit, and a winning profit margin (unrealized profit margin). The total profit / loss of investment products is the sum of trading profit / loss and unrealized profit / loss. Therefore, the total profit / loss is affected by these evaluation indicators.

(Effect of decomposing total profit and loss)
Whether the profit obtained from the investment product is an unrealized profit or a fixed profit (the most rough evaluation method), of course, the effect of the cash ratio on the profit and loss, the compound profit effect that the profit calls for profit, etc. are verified and turned. By comprehensively looking at the power, the profit rate of winning, the loss rate of losing, etc., it is possible to identify where there are many problems and comprehensively evaluate the points that should be improved with priority, and diagnosis becomes possible.

For example, when the trading profit / loss is large, the winning profit margin is high, and the losing loss ratio is kept low, but the unrealized loss is greatly inflated. There is a big problem with unrealized loss, and there are improvements, so it is an example that it is necessary to focus and evaluate them in more detail.

For example, if the unrealized profit is large, you buy carefully selected stocks at a good timing, and the winning profit margin (unrealized profit margin) is high, but there are still many stocks with unrealized losses, and the turnover is not working at all. , Make a profit and loss (stop-loss insurance, etc.), improve the efficiency of funds, and increase the turning power, because there is a high possibility that better results will be obtained, so convey the necessity.

(Unrealized gain / loss)
Unrealized gains / losses refer to unrealized gains / losses, which are unrealized gains / losses calculated from the purchase price of products that have not yet been traded in the opposite direction (in the case of short sales, the sale price; the same applies hereinafter). Unrealized gain / loss usually refers to the difference between the valuation price of a product calculated by the market price and the purchase price of the product.

(Definition of terms)
Winning profit refers to unrealized profit that has not yet been realized or has not been determined.

The winning profit margin is the unrealized profit margin, and is calculated by "winning profit ÷ winning purchase price". The winning purchase price is the purchase price that constitutes the unrealized gain among the purchase price that constitutes the unrealized gain or loss (that is, the purchase price of the product that is not traded in the opposite direction).

Losing loss refers to unrealized loss that has not yet been realized or has not been determined.

The losing loss rate is the unrealized loss rate, and is calculated by "losing loss ÷ losing purchase price". The losing purchase price is the purchase price that constitutes the unrealized loss among the purchase prices that constitute the unrealized gain or loss.

The cash ratio refers to the ratio of the amount remaining as cash out of the purchaseable amount (principal + trading profit / loss + deposit / withdrawal). Deposits and withdrawals are cash that has been increased or decreased by deposits and withdrawals since the principal was put in. "1-Cash ratio" means the ratio of the holding price of the product to the purchaseable amount.

The purchase win weight is the ratio of the purchase price that constitutes the unrealized gain to the purchase price. Therefore, "1-purchase winning weight" means the ratio of the purchase price constituting the unrealized loss to the purchase price.

As expressed in the formula of FIG. 13, the unrealized profit / loss is composed of a cash ratio, a trading profit / loss, a purchase win weight, a winning rate of return (unrealized profit rate), a losing loss rate (unrealized loss rate), and the like.

Not only the trading profit / loss explained above, but also the unrealized profit / loss and the total profit / loss can be evaluated step by step.

(Specific example regarding evaluation of total unrealized gains / losses)
The advice generation unit 321 evaluates the total unrealized profit / loss.

The basic numbers are
・ Principal ・ Total unrealized gains / losses ・ Purchase price of unsold stocks (or unsold stocks) ・ Current valuation of unsold stocks (or unrepurchased stocks) ・ Elapsed days ・ Number of winning stocks held ・ Winning stocks held Total unrealized profit in case ・ Winning purchase price of owned stock ・ Number of lost stocks held ・ Total loss in case of losing owned stock ・ Trading price of losing stock held ・ Number of purchases ・ Number of stocks held ・ Average number of days held And so on.

The evaluation index is
・ Rotational power / principal growth rate (= (purchase price + cash) ÷ (principal + deposit / withdrawal))
・ Annual principal growth rate (= principal growth rate ÷ elapsed years)
・ Average number of days held ・ Profit / loss ratio (= total unrealized profit / loss ÷ total purchase price)
・ Win rate (= number of wins ÷ number of purchases)
・ Profit per win (= profit in case of win ÷ number of wins)
・ Profit margin in case of winning (= profit in case of winning ÷ purchase price in case of winning)
・ Stock occupancy rate ・ Winning stock occupancy rate ・ Losing stock occupancy rate ・ Profit and loss composition ratio (by brand)
・ Average rate of increase / decrease (annual conversion)
・ There are unrealized gain / loss weights, trading gain / loss weights, Nikkei average rate of increase / decrease, etc.

(Details of evaluation figures for unrealized gains and losses)
As shown in FIG. 13, the unrealized gain / loss can be evaluated by, for example, five-step evaluation values having different levels of detail.

The function with the degree of detail 1 is represented by a calculation formula including a trading history. That is, in the server 3, the advice generation unit 321 may calculate an evaluation index including trading profit / loss from the basic numerical value as an evaluation index regarding unrealized profit / loss, and generate information indicating the calculated evaluation index.

The function of the degree of detail 2 is expressed by a formula including a trading profit, a winning rate of return (unrealized rate of return), or a losing loss rate (unrealized loss rate). That is, in the server 3, the advice generation unit 321 calculates an evaluation index including a trading profit / loss and a winning profit rate or a losing loss rate from the basic numerical value as an evaluation index regarding the unrealized profit / loss, and provides information indicating the calculated evaluation index. May be generated.

The function of the degree of detail 3 is expressed by a formula including a trading profit, a cash ratio, a winning rate of return (unrealized rate of return), or a losing loss rate (unrealized loss rate). That is, in the server 3, the advice generation unit 321 calculates an evaluation index including a trading profit / loss, a winning profit rate or a losing loss rate, and a cash ratio from the basic numerical value as an evaluation index regarding the unrealized profit / loss, and the calculated evaluation index. Information indicating that may be generated.

The function of the degree of detail 4 is expressed by a formula including a purchase win weight, a principal, a trading profit / loss, a cash ratio, a winning rate of return (unrealized rate of return), and a losing loss rate (unrealized loss rate). That is, in the server 3, the advice generation unit 321 calculates an evaluation index including a trading profit / loss, a winning profit rate or a losing loss rate, a cash ratio, and a purchase winning weight as an evaluation index regarding unrealized profit / loss. , Information indicating the calculated evaluation index may be generated.

The calculation formula of the degree of detail 5 is as shown below.

Unrealized gain / loss = Purchase win weight x (1-Cash ratio) x (Principal + Trading profit / loss) x Winning rate of return + (1-Purchase winning weight) x (1-Cash ratio) x (Principal + Trading profit / loss) x Loss Loss rate The formula for calculating the degree of detail 5 when there are deposits and withdrawals after the principal is invested is as shown below.

Unrealized profit / loss = purchase win weight x (1-cash ratio) x (principal + trading profit / loss + deposit / withdrawal) x winning rate of return + (1-purchase winning weight) x (1-cash ratio) x (principal + trading profit / loss) + Deposit / withdrawal) x Loss loss rate However, the winning rate of return is the unrealized profit rate, and the losing loss rate is the unrealized loss rate.

That is, in the server 3, the advice generation unit 321 evaluates the trading profit / loss, the winning profit rate or the losing loss rate, the cash ratio, the purchase winning weight, and the principal as the evaluation index regarding the unrealized profit / loss. The index may be calculated and information indicating the calculated evaluation index may be generated.

Furthermore, after evaluation according to the level of detail, each index diagnoses which index has a major problem and generates advice indicating improvement from the index with the larger problem. That is, in the server 3, the advice generation unit 321 may preferentially generate information indicating an index having a low evaluation among a plurality of evaluation indexes related to unrealized profit / loss.

Further, the advice generation unit 321 may generate information indicating diagnosis, ranking, comparison, or advice by using the evaluation index regarding the total profit / loss or the unrealized profit / loss. For example, since various evaluations are possible by calculating the evaluation index, the evaluation index may be compared with other products and the comparison result may be included in the above diagnosis, ranking, comparison, and advice.

(Evaluation, diagnosis, advice of owned products)
In the server 3, the advice generation unit 321 calculates the total purchase price (purchase price), the product evaluation price, and the benchmark evaluation price from the basic numerical values, and the total purchase price, the product evaluation price, and the benchmark evaluation. It may be compared with the amount of money to generate information indicating diagnosis or advice regarding the asset status according to the comparison result.

FIG. 14 is a diagram showing an example of an evaluation index of a owned product according to the present embodiment.

The procedure for the advice generation unit 321 to evaluate the asset status of the product owned by the user, that is, the product that has not been counter-sold after the purchase (in the case of short sale), is shown below. Comprehensive evaluation of owned products can be performed by the following procedure.

(S1) The advice generation unit 321 calculates "purchase price x rate of increase / decrease of the product" of each owned product. The rate of increase / decrease of a product is the rate of increase / decrease from the time of purchase to the present. The advice generation unit 321 calculates the rate of increase / decrease of the product by the following equation 1.

Product price increase / decrease rate = (current evaluation amount-purchase amount) / purchase amount x 100 [%] ... Equation 1
(S2) The advice generation unit 321 totals the "purchase price x rate of increase / decrease of the product" of each owned product. The total amount is used as the product evaluation amount. The product valuation amount indicates the total of the current valuation amounts for each owned product.

(S3) The advice generation unit 321 calculates "recommended buying amount x benchmark rate of increase / decrease" for each owned product. The benchmark rate of increase / decrease is the rate of increase / decrease from the time of recommended buying to the present. The benchmark is not limited to the Nikkei 225, TOPIX, etc., but may be a valuation amount by dedicated software, a stock price of a specific stock, or the like. The advice generation unit 321 calculates the benchmark rise / fall rate by the following equation 1.

Benchmark rate of increase / decrease = (Current benchmark-Benchmark at the time of recommended buying) / Benchmark at the time of recommended buying x 100 [%] ... Equation 2
(S4) The advice generation unit 321 totals the "recommended buying amount x benchmark rate of increase / decrease" of each owned product. The total amount is used as the benchmark evaluation amount. The benchmark valuation amount indicates the total of the current valuation amounts for the product, assuming that the product linked to the benchmark is purchased at the same price.

(S5) The advice generation unit 321 compares the total purchase price, the product evaluation price, and the benchmark evaluation price, and generates information indicating diagnosis or advice regarding the asset status according to the comparison result. The total purchase price indicates the total purchase price for each owned product.

Thereby, for example, when the product evaluation amount exceeds the benchmark evaluation amount, it is possible to evaluate how much the amount exceeds the benchmark evaluation amount. If the product valuation price is below the benchmark valuation price, you can evaluate how much it is below the benchmark valuation price. When the benchmark is the Nikkei 225, it can be inferred that the results are better when the Nikkei 225 index type products are managed than the actual managed products, so it is possible to diagnose that there is a problem in the selection of stocks.

In addition, even if the benchmark valuation exceeds the product valuation, there are many investment targets that have obtained better performance during the period, so by showing that performance, better performance can be achieved. Can provide tips and advice to get. For example, if the stock B is held for the relevant period, the performance of the stock B is three times higher than that of the stock A, which is a good example of hints and advice.

(Pattern classification of owned products)
FIG. 15 is a diagram showing an example of a pattern of owned products according to the present embodiment.

In the server 3, the advice generation unit 321 acquires the unopposed trading data from the trading data, and uses the unopposed trading data as the current price, the buying price, the rate of increase / decrease of the investment product held, and the rate of increase / decrease of the benchmark. It is classified into the corresponding patterns, the purchase price or product valuation amount for each pattern is calculated from the non-reverse trading data, and the diagnosis regarding the asset status or the asset status according to the ratio of the purchase price or product valuation amount for each pattern is performed. It may generate information that provides advice.

First, the advice generation unit 321 classifies the patterns of each owned product. The advice generation unit 321 classifies the products owned by the user into the following four patterns. That is, in the winning pattern 1, the current price is larger than the buying price, and the rate of increase / decrease of the stock is larger than the rate of increase / decrease of the benchmark. In the winning pattern 2, the current price is larger than the buying price, and the rate of increase / decrease of the stock is less than the rate of increase / decrease of the benchmark. In the losing pattern 1, the current price is less than the buying price, and the rate of increase / decrease of the stock is larger than the rate of increase / decrease of the benchmark. In the losing pattern 2, the current price is less than the buying price, and the rate of increase / decrease of the stock is less than the benchmark rate of increase / decrease.

Next, the advice generation unit 321 calculates the total purchase price or the product evaluation amount for each of the above four patterns, calculates the ratio of the amount of money for each pattern to the total of the four patterns, and the ratio of each pattern or which pattern. Diagnose or generate advice depending on whether the amount is the largest.

For example, when the winning pattern 1 is 70% and the winning pattern 2 is 30%, the advice generation unit 321 diagnoses that "it is above the average, and the brand to buy and the timing to buy are good". See the indicator of what you are doing. "

Further, when the winning pattern 2 is 80%, the winning pattern 1 is 10%, and the losing pattern 1 is 10%, the advice generation unit 321 diagnoses that "profit is generated, but the benchmark is not exceeded." Generate advice that "there is a lot of room for improvement. I want to aim for results that exceed the average."

Further, when the losing pattern 1 occupies 80%, the advice generation unit 321 says, "Although I have lost, the benchmark is down. For that reason, the loss is kept small. Diagnosis that the benchmark is losing as the benchmark goes down, such as ".", "However, it is still recording a loss, and the loss is cut early, etc. It is important not to continue "to generate advice that recommends early stop-loss.

In addition, when the loss pattern 2 accounts for 90%, it is recommended to improve both the diagnosis that "the unrealized loss is a big drag" and "the buying timing and the selection of the brand. The loss cutting technology is also important. I want to learn not only the selection of stocks and the timing of buying, but also the loss cut in case of failure at an early stage. "

(Effect of evaluating unrealized gains / losses)
The following effects can be achieved by including trading profit / loss in the components of unrealized profit / loss and adding it to the evaluation target.

First, the unrealized profit / loss is greatly affected by the already fixed loss and profit (trading profit / loss), and if the fixed profit is large, the purchase price will increase. According to this, when the trading profit is large, there is an effect that a larger profit can be obtained even with the same rate of return. On the contrary, when the trading profit / loss becomes negative, the purchase price decreases, so that the profit becomes smaller even with the same rate of return.

(Principal + trading profit / loss) ÷ principal or (principal + trading profit / loss + deposit / withdrawal) ÷ (principal + trading profit / loss) is one index showing how much the principal is increased by trading profit / loss. Is. Since the purchase amount, which is one of the factors that make up the unrealized gain / loss, is expressed by (principal + trading profit / loss-cash balance), these indicators are the factors that greatly influence the unrealized gain / loss.

According to the above, by clarifying that the increase or decrease in trading profit or loss has a large effect on profit or loss, the so-called compound interest effect becomes clear and quantifiable in the evaluation and diagnosis of investment profit or loss.

In addition, the purchase win weight and the cash ratio are important evaluation indicators, and it is important to increase the purchase win weight among the owned products. As with trading profit and loss, it is also important how large the difference between the winning rate of return (unrealized rate of return) and the losing loss rate (unrealized loss rate) is, and it is added to the evaluation target. As a result, even if the unrealized gains and losses are the same, multifaceted evaluation and diagnosis can be performed.

In addition, if the cash ratio is too high, opportunity loss will occur and the unrealized gain that would have been originally obtained can be estimated, which is also an important factor for evaluation. Opportunity loss can be calculated by "cash x unrealized profit / loss ratio". In addition, the winning rate of return (unrealized rate of return), the losing loss rate (unrealized loss rate), and the difference between them are important factors for managing unrealized gains and losses and are subject to evaluation. If you have a lot of unrealized losses and exceed the trading profit and loss, the problem is still big and you should improve it first.

For example, it is important to learn how to increase the winning profit margin and how to reduce the losing loss rate (unrealized loss rate), which enables multifaceted evaluation.

Diagnosis can be made based on these evaluation values. Then, various comparisons such as comparison with others and comparison with the average become possible. Ranking is possible, and ranking is also possible. As a result, advice based on the evaluation / diagnosis comparison ranking becomes possible.

[Embodiment 2]
The second embodiment of the present invention will be described below. For convenience of explanation, the same reference numerals are given to the members having the same functions as the members described in the first embodiment, and the description thereof will not be repeated.

In the present embodiment, not only the evaluation of the actual trading but also the user performs a virtual trading (simulation) based on the past actual stock price and the event, and the advice generation unit 321 of the server 3 relates to the virtual trading. Make an evaluation. That is, unlike the case of actual trading data, the user makes a trading decision according to a past stock price or an event in a format of answering a question displayed on the terminal 2. Then, the evaluation of buying and selling and profit / loss by the advice generation unit 321 branches according to the individual judgment of the user.

Specifically, the server 3 generates information on virtual trading of investment products in the past. In the server 3, the advice generation unit 321 acquires the initial conditions including the start time of the virtual trading and the holding status of the investment product and cash assumed at the start time. Then, the advice generation unit 321 sequentially generates two or more question screens including the date of the event that occurred after the start time and the question and option regarding the buying and selling of the investment product, using the initial condition.

In addition, the question screen may further include an event.

In addition, the question screen may further include the valuation amount of the investment product and the assets held including cash on the date of the event.

Further, the advice generation unit 321 may set the valuation amount of each investment product as 100 on the date of the first event and calculate the valuation amount of each investment product on the date of the second and subsequent events as an index against 100. good.

FIG. 16 is a diagram showing an example of an initial screen of a stock investment simulation (virtual trade) according to the present embodiment. As shown in FIG. 16, the terminal 2 displays the initial screen of the stock investment simulation. When the user clicks the "Start" button displayed on the initial screen, the terminal 2 starts the stock investment simulation.

FIG. 17 is a diagram showing an example of a question screen of the stock investment simulation according to the present embodiment. As shown in FIG. 17, the terminal 2 displays a question screen of the stock investment simulation. The question screen displays events, dates, questions, hints, elapsed time, assets held, and choices. The event indicates what is happening at that time. The date indicates the date when the event occurred. The question indicates a problem for the user. The hints give detailed investment advice, which is different from the event. The elapsed time indicates the time elapsed since the start of the stock investment simulation. The owned asset indicates the amount of the asset currently held by the user. There are four options for the question, for example, A. Sale of J company shares, B. Holding of Company J shares, C.I. Switching from J company stock to K company stock, D. Switching from J company stock to L company stock is listed.

The process will be described below. The process includes initial conditions, question 1, and a result report.

(Initial condition)
The initial conditions include the date, holding status (stock name and number of shares, cash), and initial valuation. The initial valuation is the valuation of all assets, including stocks and cash. The initial conditions may be set by the user or the server 3 may hold the default conditions.

A specific example of the initial conditions is shown below.
-Define date 0 as the starting point of the stock investment simulation.
-Case of 4 holdings (A, B, C, D) -The number of shares of A is a1 shares, B is b1 shares, C is c1 shares, and D is d1 shares.
・ Initial evaluation value α (for example, 4 million yen)
It may be converted by the actual number of shares, or the valuation amount of each stock at the time of starting the stock investment simulation may be indexed to 100. The user may start the stock investment simulation with only cash held, or may hold both cash and stocks at a predetermined ratio.

FIG. 18 is a diagram showing a transition of a stock price in a stock investment simulation according to the present embodiment. FIG. 18 shows the actual stock price and the simulated stock price on the date of each event. The actual stock price is literally the actual stock price. The simulated stock price is a stock price represented by an index, and the stock price of each stock on June 23, 2016 is set to 100, and after that, the stock price of each stock is represented by an index to 100.

FIG. 19 is a diagram showing changes in the valuation amount for each branch of each question in the stock investment simulation according to the present embodiment. The valuation amount of each issue on June 23, 2016 is set to 100, which is the first reference index. Further, the valuation amount of each issue at the time of branching of Question 2 on November 9, 2016 is the valuation amount of a certain issue, which is 91, which is an index for 100. These make it easier to evaluate which brand should have been bought at that time by looking at the subsequent changes in the valuation amount.

For example, when a brand is replaced from company G to company E, cash is actually left over. This would be complicated, so it is assumed that all the sale price has been transferred to Company E. Therefore, on November 9, 2016, the evaluation value of Company E will be 91. Actually, if cash is left over, the valuation amount 91 is a breakdown of company E 80 and cash 11. The valuation amount of 91 is a case where cash is assumed to be 0, but if it is performed more realistically, it is possible to assume a case where cash is surplus.

The above case assumes that all the proceeds from the sale will be used to fund the purchase, but due to the unit stock, the case where cash is actually surplus is a more realistic case. In that case, the cash balance moves when the issue is replaced, and such a case can also be displayed.

Each question will be explained below. The dates for each question (questions 1 to 5) are 2016/6/23, 2016/11/9, 2016/12/7, 2016/12/27, and 2018/2/9, respectively.

(Question 1)
・ Date 1 (2016/6/23)
・ Valuation value β (total valuation amount calculated based on the stock price of each stock A, B, C, D as of date 1)
・ Explanation of the status of issue A and presentation of options ・ Explanation of the status of the entire market and the status of issues that require judgment on that day ・ 4 case options In the case of holding an issue, selling issue A, maintaining ownership of issue A, E An example is switching to a brand and switching to an F brand. When starting a stock investment simulation using only cash, purchase of stock A, cash holding, purchase of other stocks, etc. are examples of options.

(Question 2)
・ Date 2 (2016/11/9)
・ Holding ・ Explanation of the status of B brand and presentation of options ・ 4 case options (Sale of B brand, holding of B brand, transfer to G brand, transfer to H brand)
(Question 3)
・ Date 3 (2016/12/7)
・ Explanation of the status of C brand and presentation of options ・ 4 case options (Sale of C brand, holding of C brand, transfer to I brand, transfer to J brand)
(Question 4)
・ Date 4 (2016/12/27)
・ Explanation of the status of D brand and presentation of options ・ 4 case options (Sale of D brand, holding of D brand, transfer to K brand, transfer to L brand)
(Question 5)
・ Date 5 (February 9, 2018)
・ Two-case options (sale of owned stocks, postponement of sale of owned stocks)
According to the answers to questions 1 to 5, 4 × 4 × 4 × 4 × 2 = 512 ways of evaluation are calculated.

The stock price of each stock on each date is 1A as "the closing price of stock A on the date of question 1" and 2C as "the closing price of stock C on the date of question 2", and so on. The stock prices at the start of the stock investment simulation are 0A, 0B, 0C, and 0D.

The advice generation unit 321 calculates the valuation amount (index base) of all patterns, assuming that the index at the start of each issue is 100.

First, the advice generation unit 321 calculates the four evaluation values as of the date 1 of question 1 as follows.

(1) Case where A brand is sold Total of 1A x a1 (cash), 1B x b1, 1C x c1, 1D x d1. Or, if it is an index base, it is the total of 100 × 1A / 0A, 100 × 1B / 0B, 100 × 1C / 0C, and 100 × 1D / 0D.

(2) Case of continuing to hold A brand The total of 1A x a1 (A brand), 1B x b1 (B brand), 1C x c1 (C brand), and 1D x d1 (D brand).

(3) Case of switching from A brand to E brand 1E × e1
E issue (number of E issue shares calculated by 1A x a1 ÷ 1E: e1 share)
The total of 1B × b1, 1C × c1, and 1D × d1.

(4) Case of switching from A brand to F brand 1F x f1
F issue (number of F issue shares calculated by 1A x a1 ÷ 1F: f1 share)
The total of 1B × b1, 1C × c1, and 1D × d1.

Next, the advice generation unit 321 calculates the evaluation amount of each branch of question 1 at the time of question 2 as follows.

(1) Case where A brand is sold Total of 1A x a1 (cash), 2B x b1, 2C x c1, and 2D x d1. If it is an index base, it is the total of 100 × 1A / 0A, 100 × 2B / 0B, 100 × 2C / 0C, and 100 × 2D / 0D.

(2) Case in which A brand continues to be held Total of 2A x a1 (A brand), 2B x b1, 2C x c1, and 2D x d1.

(3) Transfer to E brand 2E × e1
E issue (number of E issue shares calculated by 1A x a1 ÷ 1E: e1 share)
The total of 2B × b1, 2C × c1, and 2D × d1.

(4) Transfer to F brand 2F x f1
F issue (1A x a1 ÷ 1F, calculation of the number of F issue shares: f1 share)
The total of 2B × b1, 2C × c1, and 2D × d1.

Similarly, the advice generation unit 321 calculates the valuation amount for each combination by setting the stock price of the stock held or the stock purchased to the stock price on the dates of questions 3 and 4. As a result, it is possible to grasp the transition of the valuation amount of the brand.

For example, in the case of Case 3 of Question 1, since the A issue is switched to the E issue, the valuation amount changes with the stock price of the E issue thereafter. For example, in the case of Case 3 of Question 2, since the B issue is switched to the G issue, the valuation amount changes with the stock price transition of the B issue at first, but after the transfer, the valuation amount changes with the stock price of the E issue.

In this way, four types of changes in the valuation amount are formed for each question. Therefore, depending on this combination method, there are 512 combinations in this case. That is, when the user answers each question, it branches in 512 ways.

The valuation amount changes in each time series, and the result of how much it finally became is also branched into 512 ways.

According to the above, it is possible to calculate the valuation amount of the four cases of Question 1 and grasp the transition. It is possible to calculate the evaluation value of the four cases of Question 2 and grasp the transition. The evaluation value of 4 cases of question 1, the evaluation value of 4 cases of question 2, the evaluation value of 4 cases of question 3 and the evaluation value of 4 cases of question 4 can be calculated using the stock price at each time point.

(Concrete example)
For example, in the case of a concrete example, as the best scenario, there is a case where all three stocks other than Recruit were sold in February 2018 with the third choice. The valuation amount is 1.02 million yen.

On the other hand, as the worst scenario, there is a case where all the fourth choices are made. The valuation amount is 1.12 million yen.

In other words, 512 cases fall within the range of 1.12 million yen to 10.2 million yen. Then, the ranking of the final evaluation value can be calculated.

The best scenario is, of course, number one. The worst scenario is, of course, 512th.

The answer results include ranking ranking, final valuation amount, valuation amount transition, final holdings and cash, valuation gain, unrealized profit / loss, trading profit / loss, turning power, diagnosis result, win rate, rate of return in case of win, and case of loss. Communicate results such as loss rate, evaluation value, advice, etc.

(Modification example)
When you select an option according to the date, the transition of the valuation amount for that question is determined. Therefore, it is possible to track the valuation amount in chronological order. Initially, you may start with just cash. In order to clarify the compound interest effect, the question may be further branched, such as what to do with the issue whose issue was replaced in the question. This is just an example, and the number of questions may be small or large.

As the number of questions increases, the opening becomes larger, the number of branches increases, and the number of combinations increases. The more choices you have in a question, the closer it is to reality and the more combinations you have.

Judgments of multiple stocks may be included on the same date, or some may be sold. Short sales and ETFs may be included.

(Learning process)
Depending on the evaluation, you may be guided to e-learning materials to reinforce weaknesses. For example, in the case of an evaluation in which profit-taking sales are fast, the turning power is too high, and the trading results are not improved, the teaching materials related to them are collated in the database, and learning is promoted through the provision of links and contents.

In the advice presentation system 1, students are asked to learn learning and theory to reinforce weaknesses according to the evaluation, and through the learning, the practice is changed, the buying and selling changes, and the evaluation changes.

E-learning has a mechanism that cannot be advanced unless the test and confirmation test are advanced. In cooperation with such a mechanism, after reinforcing weaknesses and encouraging learning, the system will be linked to improve investment results by conducting practical buying and selling again.

According to the above, it is possible to provide a learning path to the user when the user does not know what to learn or how to improve.

(Effect of Embodiment 2)
The user can experience how the outcome (evaluation amount) changes, the evaluation diverges, and the ranking changes depending on the individual buying and selling decisions. In addition, users can understand and experience the process of dynamically changing personal assets and widening investment inequality. That is, it is possible to make the user realize that the individual buying and selling decision has a great influence on the investment result.

As a result, it is possible to motivate the user to learn about asset management and further create the effect of learning.

[Embodiment 3]
Embodiment 3 of the present invention will be described below. For convenience of explanation, the same reference numerals are given to the members having the same functions as the members described in the first and second embodiments, and the description thereof will not be repeated.

In this embodiment, the comprehensive diagnosis performed by the advice presentation system 1 will be described.

(Definition of total profit and loss and comprehensive diagnosis)
The total profit / loss is the total profit / loss of the unrealized profit / loss and the trading profit / loss. Comprehensive diagnosis refers to a diagnosis that combines individual diagnoses for total profit / loss, unrealized profit / loss, trading profit / loss, etc.

The advice generation unit 321 makes a comprehensive diagnosis of the user's trading status by combining the total profit / loss, the unrealized profit / loss, and the individual diagnosis of the trading profit / loss.

(Significance of comprehensive diagnosis)
The outcome of an investment is actually a combination of multiple factors. A high rate of return on a win usually means a low turnover when winning. On the contrary, when the loss rate of losing is low, the rotational force is high. Comprehensive diagnosis of these complex factors is important for looking at the whole.

For example, the larger the trading profit, the more it affects the composition of unrealized profit, and the compound interest effect becomes clearer. On the contrary, if there is no trading profit, no matter how high the unrealized profit margin is, the funds will not increase more than expected. In some cases, even if the winning profit margin is low, it can be covered by the high rotational force. Each element has a complex influence on the other.

For example, if the combined condition that the winning rate is low, the winning profit rate is high, and the losing loss rate is low, the operation is very good. If the winning rate is low, the winning profit rate is low, the losing loss rate is low, and the "winning profit rate + losing loss rate" is negative, the assets are greatly reduced depending on the number. Comprehensive diagnosis is very important because even if the other numbers are the same, even if one number is small, the diagnosis result will be completely different.

(Effects of comprehensive diagnosis and specific examples)
Even if the result of the individual diagnosis is not known, the comprehensive diagnosis can be obtained by combining the results of a plurality of individual diagnoses.

For example, with regard to trading profit, if the profit is ± 0, but unrealized profit is formed, and if it wins, the holding period is extended, only good stocks remain, and bad stocks are closed early. Even if you look at the result of only the trading profit and loss, the diagnosis is wrong. It is an example that an appropriate diagnosis is made only after making a comprehensive judgment including diagnosis of unrealized profit and loss and analysis of winning patterns.

Even if the turning power is high, the holding period is short, and the winning profit rate and the losing loss rate are low, there are some people who earn at the winning rate and are able to operate well. One specific example is that the overall diagnosis result will be good if there are other prominent parts, even if the diagnosis is not very good individually.

These specific examples have the opposite diagnosis results to the individual diagnosis results, which is the reason why a comprehensive diagnosis is necessary.

(Comprehensive diagnosis process)
Unrealized gains and trading gains, which are total profits and losses, are formed by intertwining various factors. The annual rate of increase in principal is determined by more complex and complex factors, and even if the same results are achieved, there are various types and various backgrounds. Diagnosis by multiple factors is indispensable for situation analysis, and the process is diagnosed by combining various evaluation indexes.

(About diagnosis by type)
One method of comprehensive diagnosis performed by the advice presentation system 1 is type-specific diagnosis. In the process of diagnosis by type, the advice generation unit 321 calculates various evaluation indexes, determines a combination of the evaluation indexes (range of two or more evaluation indexes), and then uses the user according to the numerical value of the evaluation index. Classify the trading status of.

It is possible to categorize the trading situation categorically according to the combination of various indicators. The type that is the result of classification is defined as a type.

There are various types. Large classification is possible, and fine classification is possible. The factors necessary to determine the type are various evaluation indexes such as the above-mentioned rotational force and winning profit margin. Types can be classified according to how various evaluation indexes are combined.

The reason why each type is decided is that it can be applied to the type to some extent depending on how the evaluation indexes are combined. Just by changing the number of the partition, it may change from A type to B type, but it will be possible to clearly classify the divisions that were not clear until now by the numbers, and it will be possible to manage each type.

(Specific example of type classification)
The short-term day trading type has a very high turning power, the number of days of principal turning is one to several days, the winning profit margin and the losing loss ratio are sufficiently small, and the winning percentage is the decisive factor for profitability.

The short-term swing trading type has high turning power, the principal turning days are about one week (4 to 14 days, etc.), and the winning profit margin and losing loss ratio are as small as around 5%, and the winning percentage is also profitable. It is the decisive type.

The large price range type is a type in which the turning power is low, but the assets are increasing because the winning profit margin overwhelmingly exceeds the losing loss ratio.

The long-term deferred type has a low turning power and an average holding period of more than 360 days, and the unrealized profit / loss is more important than the trading profit / loss. The loss rate (unrealized) is also large, and it is a type that has not been sold.

The salted type has a low rotational force, a high loss loss rate, a low winning profit rate, and an unrealized loss.

What is important is that the types can be divided according to the combination of evaluation indicators and can be drawn by objective numbers. It may be derived by combining a plurality of lines shown in each individual diagnosis.

For example, the evaluation value with the rotational force diagnosis is within 3 days, and the high weight (50% or more) in the winning pattern analysis is pattern 1. Anyway, it is a type that has achieved good results by the operation that makes the rotation effective, and it is positioned as a high rotation type of the forward tension type.

Various combinations are possible, and the combination method is free and many types can be created. The various evaluation indexes that are the basis of individual diagnosis can obtain sufficient diagnostic results by themselves, but by utilizing the combination, deeper analysis becomes possible and the diagnosis becomes deeper and more precise. ..

For example, in the individual diagnosis, the rotational force is between 7 and 30 days, the winning profit margin exceeds 20%, and the losing loss ratio is suppressed to 10% or less. There are a total of 200 people in this type, and all of them have a high rate of increase in principal, 70% of the people have an annual rate of 20% or more and their assets are increasing, and the average annual rate is 25%. Can be diagnosed and analyzed.

(Effect of diagnosis by type)
The effect brought about by the type-based diagnosis is that the user's own type becomes clear, it is easy to compare with others, and the user may know that there are various methods. In particular, there is an effect that the user's own standing position is clarified by comparison and ranking with people of the same type, and a guidepost to be improved can be created.

(Ranking by type, comparison)
One method of comprehensive diagnosis performed by the advice presentation system 1 is comparison and ranking of evaluation values including the rate of increase / decrease in principal among types grouped by a plurality of factors. The advice generation unit 321 compares and ranks the above-mentioned evaluation numerical values of users for each type classified according to the numerical values of a plurality of evaluation indexes.

By ranking and comparing the above evaluation values for each type, it is possible to compare and rank the above evaluation values among groups doing the same method.

In a similar way, it will be possible to learn from others how to move in the better direction. For example, those who are getting good results in swing trading type refer to which number is good.

(Ranking by type, effect of comparison)
By calculating the above evaluation values for each type, it is expected that it will be clear which type is superior and which type is inferior. As a result, for example, the average principal increase rate (annual rate) of the swing trading type was 10% on average, but the average principal increase rate (annual rate) of the large price range type was 25% on average, and those who failed. It is possible to derive results such as less.

For example, if the number of the person who gives the best result of the above types has a very high win rate, a high rate of return, and a winning pattern of 1 is the majority, the user is compared to his own number. , It will be possible to improve the inferior numbers. In addition, although it was a good ranking in the whole, it is easy to compare with others such as average numbers in the user's own type, and deeper analysis becomes possible.

(Example of diagnosis result report)
The following is an example of a report of the diagnosis result for the user's trading status. In the following, (dynamic change) refers to a text or a numerical value that dynamically changes according to the transaction data of the user.

An example of a comprehensive diagnosis result report is shown below.
◎ Comprehensive diagnosis ☆ Diagnosis by type It was judged that the trade type of Mr. A was a swing trade type (dynamic change).
☆ Description of type Swing trading type (dynamic change) is a short-term swing trading type, which has high turning power and principal rotation days of about one week (4 to 14 days, etc.), winning profit margin and losing. The loss rate is as small as around 5%, and the winning rate is also the decisive factor for profitability.
☆ Your ranking in the swing trading type (principal increase / decrease rate (annual simple interest) is 3rd out of 100 people (dynamic change)).
☆ Type ranking (compared with the average value of principal increase / decrease rate (annual simple interest))
25th out of 50 types (dynamic change)
☆ Your overall ranking is 250th out of 1000 (dynamic change).
☆ Combination diagnosis Calculation formula for trading profit and calculation formula for unrealized profit / loss (dynamic change)
☆ Comparison with average value (dynamic change)
☆ Excellent numerical value (dynamic change)
☆ Inferior numerical value (dynamic change)
☆ Comprehensive diagnosis result (dynamic change)
It is very good at 3rd place in the swing trading type, but it is 250th out of 1000 people in the whole, so there seems to be plenty of room for improvement.

Especially good numbers are turning power and winning percentage, and inferior numbers are the result of low winning profit margin.

The following is an example of a report of individual diagnosis results.
◎ Individual diagnosis ☆ Rotational force diagnosis Diagnosis result (dynamic change)
Evaluation numerical table (dynamic change)
Explanation (dynamic change)
☆ Winning profit margin diagnosis ☆ Losing loss rate diagnosis ☆ Winning pattern analysis ☆ Losing pattern analysis ☆ Trading profit / loss analysis ☆ Unrealized profit / loss analysis ☆ Comprehensive profit / loss analysis [Embodiment 4]
Hereinafter, Embodiment 4 of the present invention will be described in detail. For convenience of explanation, the same reference numerals are given to the members having the same functions as the members described in the first, second, and third embodiments, and the description thereof will not be repeated. Further, the contents of the comparison result, ranking result, diagnosis result, advice and the like shown below are only examples and do not limit the present invention.

(Information presentation system 10)
The information presentation system 10 according to the present embodiment will be described with reference to the drawings. FIG. 20 is a diagram showing a configuration of an information presentation system 10 according to the present embodiment. As shown in FIG. 20, the information presentation system 10 includes a terminal (terminal device) 2 and a server (information generation device) 30. The terminal 2 and the server 30 are configured to be communicable via the network 4.

The terminal 2 acquires trading data by user operation, reading from a recording medium, or the like, and displays various results according to the trading data. For example, a PC, a tablet terminal, a smartphone, or the like. The server 30 generates various results regarding the buying and selling of investment products. The network 4 is a network including the Internet. Investment products include stocks (including Japanese stocks and overseas stocks), investment trusts, exchange-traded funds (ETFs), and foreign exchange margin trading (FX).

FIG. 20 is also a block diagram showing the configurations of the terminal 2 and the server 30 according to the present embodiment.

(Terminal 2)
As shown in FIG. 20, the terminal 2 includes a communication unit 21, a control unit 22, a display unit 23, and an operation reception unit 24. The details of each part are the same as those in the first embodiment.

(Server 30)
As shown in FIG. 20, the server 30 includes a communication unit 301, a control unit 302, and a storage unit 303. The communication unit 301 is a unit that communicates with the terminal 2. The control unit 302 controls the entire server 30, and is, for example, one or a plurality of processors. The storage unit 303 stores data according to the instruction of the control unit 302, and is, for example, a hard disk device, a flash memory, or the like.

The control unit 302 includes an information generation unit 3021. The information generation unit 3021 acquires the trading data of the investor (or investment product), generates the trading data to be aggregated from the acquired trading data, extracts and processes the trading data to be aggregated, and creates the profit / loss level trading data ( It is possible to have it in the previous process), calculate the evaluation index by referring to the profit / loss level trading data, and generate information to display the calculated evaluation index. Next, the information generation unit 3021 makes a comparison with reference to the evaluation index, and generates information indicating the result of the comparison. Ranking is performed with reference to the evaluation index, and information indicating the result of the ranking is generated. A diagnosis is made with reference to the evaluation index, and information indicating the result of the diagnosis is generated. Then, the information generation unit 3021 generates information indicating advice according to the evaluation, comparison, ranking, diagnosis result, and the like. The information generation unit 3021 displays the generated information by various methods, generates and distributes article information and the like.

The display of the evaluation index here means to calculate each evaluation index from the trading data and display the evaluation index. The evaluation here means to calculate and evaluate each evaluation index from the trading data. Comparison refers to comparison with others using the calculated evaluation index. Ranking refers to ranking based on evaluation indicators. Diagnosis refers to diagnosing what kind of buying and selling has been done based on the evaluation index. Advice refers to giving advice based on evaluation results, comparison results, ranking results, and diagnosis results. The display here refers to displaying the results of evaluation indicators, evaluations, comparisons, rankings, diagnoses, advice, and the like. Generating and distributing article information refers to generating and distributing the results of evaluation indicators, evaluations, comparisons, rankings, diagnoses, advice, etc. as article information. However, the processes of display, evaluation, comparison, ranking, diagnosis, and advice of evaluation indicators are not all essential, and at least one may be provided.

First, the system is shown. The preparation phase is the first step, which is a pre-stage for accurate processing in the information processing system. See FIG. 101 for the first phase. See FIG. 102 for the second to fourth phases. Refers to the fifth to twelfth steps.

(First step)
The first step is a step of acquiring trading data, that is, a step of acquiring trading data including trading data from a securities company, a user, or the like. Normally, the trading data collected here is targeted for the next processing. Of course, in the case of a trading agency such as a securities company, this acquisition step may be few (or not).

The first step includes storing the trading data in the DB of the storage unit 33. In addition, the first step includes issues given by the user, an administrator or the like determining and requesting an article to be delivered. The first step may include a phase of processing into a certain format. Normally, since the format such as a CSV file contains buy / sell data, the purchase data and the sale data are made to face each other, and the market price or the like is assigned to the data that does not face each other. The first step may include a display phase or may include an AI phase.

(Second step)
The second step is a step of creating trading data to be aggregated, and is a step of collecting a plurality of acquired trading data or extracting and classifying and totaling based on a certain standard. The second step may include a phase of increasing or decreasing data items as needed. The second step may include, for example, a phase of increasing the number of securities company items, the number of reference medium items, and the number of technical index values. These data items are basically associated with purchase data, sale data, and the like. Processing phases such as calculation of total value, calculation of average value and maximum value, calculation of composition ratio, etc. may be included.

The second step includes storing the aggregated trading data in the DB of the storage unit 33. The trading data to be aggregated may be managed in another table and linked when necessary. For example, other tables include an investment target table, an investor table, a performance upward revision table, a technical indicator table, an investment type table, and the like. Prepare a separate table that includes the same items as the trading data items (for example, brand code, brand code and purchase date), link them with common items, and aggregate the information managed in the separate table. Can be included in the item of. Then, the aggregated trading data can be used as an extraction condition by the information processing system or as a component (component trading data), and can be expected to be used for various purposes.

The buying and selling data may include buying and selling items as a unit for buying and selling, or may create and manage separate items for selling and buying. There is a mixture of data in which buy and sell items are lined up and buy data that has not yet been sold, with buy and sell as one unit, but even if it is a rule to enter the market price and data for the day for data that does not have counter-trade. good. The second step may include a machining phase. Further, the extraction condition of the trading data to be aggregated by the information processing system may be one, or may include all general extraction patterns by the information processing system such as OR and AND.

The second step may include a display phase or an AI (machine learning, intelligent calculation, etc.) phase.

(Third step)
The third step is a step of creating trading data for each component, and is a step of further classifying the trading data to be aggregated by component, extracting, classifying, and totaling. The third step may include an aggregation phase in which the components are classified by component, the total value or the average value is calculated for each component, or the component ratio is calculated. The third step includes storing the trading data for each component in the DB of the storage unit 33. The trading data by component of Mr. A is defined as the trading data by component, which is the trading data in which the investor classifies and processes the trading data to be aggregated by the investor by the brand. After classification, the trading data by component may be further narrowed down by the extraction conditions, or may be aggregated. The third step may include a display process or an AI (machine learning, intelligent calculation, etc.) process.

(4th step)
The fourth step is a step of creating profit / loss level trading data, and is a step of determining a target profit / loss or profit / loss ratio (average ROI). If you want to target the trading profit / loss ratio, create trading profit / loss level trading data (you can have it in the previous process). The above trading data (aggregated trading data, component trading data) is further classified and extracted according to the target profit / loss (or average trading profit / loss ratio (average of ROI)). It is also possible to bring the fourth step before the third step or before the second step.

The fourth step may include a processing calculation process of aggregation for each component, total value, average value, maximum value, calculation of processing value (for example, calculation of purchase price (purchase price × purchase quantity)). The fourth step may include a process of displaying the profit / loss level trading data, or may include storing the profit / loss level trading data in the DB of the storage unit 33. The fourth step may include an AI (machine learning, intelligent calculation, etc.) process.

From the first step to the fourth step, the target profit and loss (or profit and loss ratio) to be improved, the extracted trading data, and the management items (items on the horizontal axis in the table, items on the database) Most are decided.

(Fifth step)
The fifth step is the calculation step of the evaluation index, and the factor that influences the target profit / loss (or the average trading profit / loss ratio (ROI average)) in the profit / loss level trading data created above is defined as the evaluation index. Then, it is a step to calculate those evaluation indexes. The fifth step is a step of totaling, extracting, and selecting the evaluation indexes calculated in this step, including the evaluation indexes calculated up to the fourth stage.

The first to fifth steps are the foundation. In the 1st to 5th steps, the target profit / loss to be improved (or the average trading profit / loss ratio (ROI average)) and the trading data classified / extracted (profit / loss level trading data, component trading data, aggregation target) The evaluation index (which may be a variable) that affects the trading data), management items (horizontal axis in the table), and target profit / loss (or average trading profit / loss ratio (ROI average)) is determined. The fifth step may include a machining calculation process or a display process. The fifth step includes storage of the storage unit 33 in the DB. The fifth step may include an AI (machine learning, intelligent calculation, etc.) process.

(Sixth step)
The sixth step is an evaluation step of the trading status and holding status of the target. The sixth to tenth steps are in no particular order and are not indispensable steps. The sixth step is a step to determine how much the target trading data is worth, and the information processing system examines the good points and bad points, and the information processing system determines the value. It is a step to evaluate the target. The sixth step is to evaluate the current situation, past situation, etc. by expressing the state with an evaluation index for improving the target profit and loss.

The sixth step is a step to evaluate the target profit / loss (or the average trading profit / loss ratio (mean of ROI)) using the evaluation indexes calculated up to the fifth step, and which evaluation index is used for evaluation. It is a step to decide and evaluate how to go and how to evaluate (including maximum value, average value, composition ratio, etc.). For example, if the evaluation index is trading profit / loss level trading data, the trading status is evaluated. The sixth step may include a machining calculation process or a display process. The sixth step includes storing the evaluation result in the DB of the storage unit 33. The sixth step may include an AI (machine learning, intelligent calculation, etc.) process.

(7th step)
The seventh step is a comparison step with the comparison target. In the 7th step, using the evaluation index calculated in the 5th step, which evaluation index is to be compared, which evaluation index is to be compared, and how to compare (maximum value, average value). , Including composition ratio, etc.) and compare. The seventh step may include a machining calculation phase. Of course, the seventh step includes storing the comparison result in the DB of the storage unit 33. The seventh step may include a display process or an AI (machine learning, intelligent calculation, etc.) process.

(8th step)
The eighth step is a ranking ranking step for each aggregation target from the components. The eighth step is a step in which the evaluation index calculated in the fifth step is used to determine which evaluation index is to be ranked and how to rank it, based on which criteria, and the ranking is performed. The eighth step may include a machining calculation process or a display process. The eighth step includes storing the ranking result in the DB of the storage unit 33. The eighth step may include an AI (machine learning, intelligent calculation, etc.) process.

(9th step)
The ninth step is a step of diagnosing which evaluation index is bad and which is good by using the evaluation index calculated in the fifth step. The ninth step may include a machining calculation process or a display process. The ninth step includes storing the diagnosis result in the DB of the storage unit 33. The ninth step may include an AI (machine learning, intelligent calculation, etc.) process.

(10th step)
The tenth step is an advice step (the sixth to tenth steps are not indispensable steps in no particular order), that is, the result of displaying the evaluation index up to the ninth step, the result of diagnosis, the result of comparison, and the result of evaluation. , It is a step to give advice based on the ranking result (or only in the relevant step). The tenth step shows, for example, how the target profit / loss (or average trading profit / loss ratio (average of ROI)) changes when the evaluation index judged to be bad in the diagnosis result is changed. This is a step to give advice to improve the future trading behavior of users. The tenth step may include a machining calculation process or a display process. The tenth step also includes storing the advice result in the DB of the storage unit 33. The tenth step may include an AI (machine learning, intelligent calculation, etc.) process.

(11th step)
The eleventh step is a display step (the sixth to tenth steps are in no particular order and are not indispensable steps). Up to the tenth step, the results of displaying the evaluation index, the result of advice, the result of diagnosis, the result of comparison, the result of evaluation, the result of ranking, the result of calculation of the evaluation index, etc. are as shown in FIGS. 2 and 42. It is stored in the DB of the storage unit 33 of the server 3 and is output separately.

The output results up to the tenth step are just a list of numbers, numerical results, text-based results, comparison tables, ranking data, etc., and whether these are easy to understand or understand is another matter. In order to make the content convenient, easy to understand, and easy to understand for the user, it is very important after the display step of the eleventh step.

Each step may include this display step, or it may be done together before showing it to the user. Of course, the eleventh step includes storing the display contents in the DB of the storage unit 33. The eleventh step may include an AI process or may be in the form of a table reference. In addition, the display process may be defined at each step. The eleventh step may include a machining calculation process.

(Twelve steps)
The twelfth step is an article generation and distribution step (the sixth to tenth steps are in no particular order and are not indispensable steps). Up to the tenth step, the result of displaying the evaluation index, the result of advice, the result of diagnosis, the result of comparison, the result of evaluation, the result of ranking, the result of calculation of the evaluation index, etc. are received, and the result set is shown in each figure. As shown in 2 and FIG. 42, it is stored in the DB of the storage unit 33 of the server 3 and is output separately. The result data set can be stored in the DB together with the process, used by the administrator for mail delivery and article delivery, and can be made into a blog article (12th step).

(About problem solving system and data generation system)
The first step to the twelfth step is the flow of the data generation (result) system by the information processing system from the input (cause) of the trading data. On the contrary, this is also a (cause) system in which various problems are solved by inputting a problem (result). Therefore, on the contrary, when the output results up to the twelfth step are inquired, all the answers can be obtained, which is a method of utilizing the information processing system as a problem solving system.

FIG. 64 is a diagram showing an information flow between the terminal 2 and the server 30 according to the fourth embodiment of the present invention.

FIG. 64 is a detailed description of FIG. Even in the first embodiment, in order to obtain the diagnosis result, the administrator (or the user) displays the answer of the diagnosis result from the question to the server 3. As a result, FIG. 64 stores and accumulates the relationship between the creation of trading data and the calculation of the evaluation index, the relationship between the task and the result, the relationship between the task and the creation of the trading data, and the like in the storage unit 33. It is a figure of the information processing system which shows that it can be taken out as needed. In the problem solving system, problems and trading data are created, evaluation indexes are calculated, evaluation indexes are specified, and solution results for investment problems are generated and accumulated in the storage unit 303. These are related to each other, and by accumulating the relationships in memory, the relationship that the evaluation index of set A is calculated from the trading data of A is accumulated, and the accumulation of this relationship is It can be used in various situations.

FIG. 65 is a diagram showing that the inquiry according to the fourth embodiment of the present invention is synonymous with the result of the information processing system. FIG. 65 is a process diagram from an inquiry to an answer, and is a diagram showing that the inquiry refers to various result data created by the information processing system.

FIG. 66 is a diagram showing what kind of data is accumulated according to the fourth embodiment of the present invention. FIG. 66 mainly shows the relationship between the information processing system and the storage unit. Each time the advice is generated, various data are accumulated in the storage unit 33. Such processing is the same for the process of generating result data from the input of a query.

FIG. 67 is a diagram showing a process using the hardware resource according to the fourth embodiment of the present invention. FIG. 67 is a configuration diagram of hardware and is a diagram showing how they are linked. The step of accepting the input of the user or administrator information is performed on the terminal 2.

After that, input information is transmitted to the server 3, and information such as issues and trading data is stored in the storage unit 33. Upon receiving an inquiry or input of trading data, information is extracted from the storage unit 33, and a work instruction as to what kind of work should be performed on the trading data to be aggregated is specified. With regard to trading data, trading data is created by the information processing system by determining extraction conditions, classification conditions, and aggregation conditions. The evaluation index is calculated from the trading data, and the reference to the storage unit 33 is also performed at this time. The optimum evaluation index is identified from a number of evaluation indexes, and the operation is further determined. Whether it is a display of an evaluation index, an evaluation, an advice, a ranking, or a comparison is determined, and the evaluation index is used to determine what kind of expression is to be used and how to use it. At this time as well, cooperation with the storage unit 33 is performed, and the determination is made with reference to a table or the like. Finally, the result is output, transmitted, sent to the terminal 2, receives the result, and the result is displayed by a predetermined display method. Such processing is the same not only for the problem solving system but also for the advice generation system and the article generation system.

FIG. 68 is a diagram showing a method of resolving an inquiry of the information processing system according to the fourth embodiment of the present invention. This method is the same not only for the problem solving system but also for the advice generation system and the article generation system.

FIG. 68 is a detailed description of FIG. As shown in FIG. 2, where there is input from the terminal 2 by the user or the administrator (trading data in a broad sense, investment issue data, etc.), the operation receiving unit 24 accepts the data (in the first embodiment, the management screen is displayed on these servers. We are taking the step of inputting a question and inquiring to the server 3. This input is not a special act, but an act performed by a normal administrator). The communication unit 21 of the terminal 2 transmits these data to the server 3. The communication unit 31 receives these data in the server 3. The advice generation unit 321 of the control unit 32 of the server 3 generates the received data, and after creating the trading data and calculating the evaluation index, the evaluation index data, the evaluation data, the comparison data, and the ranking. Generates data, diagnostic data, and advice data (sequentially stored in the storage unit 33). The communication unit 31 of the server 3 transmits those results to the terminal 2. The communication unit 21 of the terminal 2 receives the result, and the control unit 22 causes the display unit 23 to display the result.

In the case of trading data, as explained, processing such as extraction from trading data (creation of trading data to be aggregated), classification, etc. (creation of component trading data), aggregation, etc. (creation of profit / loss level trading data, etc.) Trading data is created, evaluation indexes are calculated, and results such as evaluation and diagnosis, advice and comparison, evaluation index results, etc. are output using the evaluation index (in the case of an administrator user, here. (It goes without saying that it may stay), it is a process of displaying the result data on the display unit 23 of the terminal 2. These are the same as the explanations so far, but the inquiry step can not answer any questions, of course, but the data calculated from the trading data is various as described in many concrete examples. You can answer various inquiries.

In the step of the problem solving system, as shown in FIG. 68, the inquiry is input (24-1) (regardless of the method such as an action normally performed by the administrator or an inquiry from the user), and the generation process is similarly performed. Finally, the display unit 23 of the terminal 2 displays the solution result of the problem (in the case of the administrator, the result set is received, and in the case of the user, the display is not all). This work instruction shows the procedure of what kind of work was performed by looking at the various data calculated in the above-mentioned second step to the tenth step from the reverse side.

If you look at a specific example, it is obvious, and the issue of "what percentage of the winning percentage" can be calculated from the trading profit / loss trading data by the number of wins / the number of trades. In the diagnosis result of Mr. A, a part of the evaluation index calculated from the trading profit / loss trading data has a relationship of the winning rate calculated by the number of wins / the number of trading.

In other words, if you look at the relationship between the trading data and the evaluation index in the direction of "trading data-> calculation of the evaluation index", or in the direction of "evaluation index-> how to extract the trading data", the inquiry can be resolved. You can.

Therefore, in the process of determining the extraction, classification, and aggregation conditions, for example, in response to the question of calculating the evaluation index, "how to extract trading data from the viewpoint of the evaluation index (classification and aggregation can be included)". Is equivalent to that. Extracting trading data is the same as the result of this evaluation index.

Therefore, in this determination process, if a table is created in which this evaluation index is output when the trading data is extracted, it is possible to determine the extraction condition that the trading data should be extracted in this way in order to calculate the evaluation index. There is a relationship (see FIG. 75). In this process, everything that can be done from the second step to the eleventh step is possible.

Therefore, the numbers, tables, and display results (for example, advice results, diagnosis results, ranking results, etc.) calculated in the second to eleventh steps are all associated by tracing how they were calculated. Is possible. The same applies to the evaluation index calculated in the first embodiment.

Winning profit The winning profit margin is derived and the diagnosis result is also obtained in relation to creating the winning profit trading data from the trading data and calculating the winning profit margin. For the problem of "I want the diagnosis result of Mr. A", the procedure to follow this process is shown. Therefore, if these are made into a database, various problems will appear and various procedures will appear. By machine learning this, we can answer various investment issues (conversely, by creating a stack that such an evaluation index can be obtained by such a procedure, the data is accumulated. This information processing system is a system that can answer many investment issues.)

FIG. 68 is a diagram showing how the inquiry is resolved. There are an inquiry input step, a trading data creation step, an evaluation index calculation step, an operation step, and a display step, and detailed explanations of each are given below. These steps are the same not only for the problem solving system but also for the advice generation system and the article generation system.

FIG. 69 is a diagram showing a processing flow of the server 3 of the information processing system according to the fourth embodiment of the present invention. FIG. 69 is a diagram showing how the processing of the server 3 is performed. This process is the same not only for the problem solving system but also for the advice generation system and the article generation system.

FIG. 70 is a diagram showing a processing method 2 of the information processing system according to the fourth embodiment of the present invention. FIG. 70 is a diagram supplementing FIG. 68 with input of trading data and the like. This processing method is the same not only for the problem solving system but also for the advice generation system and the article generation system.

FIG. 71 is a diagram showing a calculation process of the information processing system according to the fourth embodiment of the present invention. FIG. 71 is a diagram showing what kind of calculation processing is performed for a given task. For the trading data, fixed extraction conditions, classification conditions, and aggregation conditions are instructed, trading data is created, the target trading is decided from the trading data, and the evaluation index that affects the target trading is calculated. A selection is made, and the evaluation index is used to determine what kind of operation (at least one such as evaluation or advice) is to be performed, and a calculation process is performed to determine the result display. This calculation process is the same not only for the problem solving system but also for the advice generation system and the article generation system.

FIG. 72 is a diagram showing a data structure of the information processing system according to the fourth embodiment of the present invention. The characteristic of the data structure recorded in the storage unit 33 is that the trading data has a data structure in which profit and loss are calculated, and the evaluation index that affects the profit and loss, the operation that can be performed by the evaluation index (comparison, advice, etc.), and from there. It is a figure which shows that it has a series of linked data structures such as a result obtained and a method of displaying those results. This data structure is the same not only for the problem solving system but also for the advice generation system and the article generation system.

FIG. 73 is a diagram showing a reference table system of the information processing system according to the fourth embodiment of the present invention. The reference table is a table showing the correspondence between the extraction condition, the classification condition, the profit / loss status, the aggregation method of the trading data, and the necessary data.

FIG. 90 is a diagram showing a network according to the fourth embodiment of the present invention.

In the case of article data distribution, an article distribution server (regardless of the company's own company) is installed, and the division data generated by the information processing system is distributed as an article as it is, or the information data is distributed by processing.

FIG. 91 is a database-related diagram according to the fourth embodiment of the present invention. For example, there are a method of linking the purchase date and the brand code table with the trading ID and linking the RSI (Relative Strength Index) value with the relationship between the brand code and the date, and a method of linking with the purchase ID. The RSI is a method of numerically expressing the strength of price movements by utilizing the price increase and the price decrease in the market for a certain period of time, and determining whether the price is overbought or oversold. Not limited to this method, a method of associating trading data or purchase data with technical index values by some method is defined as a separate table reference method.

FIG. 92 is a diagram showing a related diagram of AI learning according to the fourth embodiment of the present invention. It is a figure which shows how the learning of AI is performed in each phase. In the first phase, the administrator or the user makes various inquiries to the information processing system, and learns the association of what extraction conditions, classification conditions, and aggregation rules should be specified for the inquiries. A concrete example is shown. In the second phase, we will learn how to select evaluation indexes in response to inquiries about the information processing system. In order to determine the most important evaluation index, we will learn how to change the 14 loess by the numerical value of the evaluation index value for inquiries by scoring. We will also learn notation fluctuations and learn to determine the evaluation index to be calculated and displayed for various inquiries. In the third step, the correspondence of which result should be displayed for the inquiry is learned. We will learn how to perform and how to perform the operation steps such as display of evaluation index, evaluation, comparison, ranking, diagnosis, advice, and generation of article data. In the fourth phase, the information processing system learns how and how to display the result set generated by the information processing system. All of the fourth phases may have these functions, or any one of them may be provided, and the case where any one of these functions is provided is defined as an AI learning system.

FIG. 93 is a diagram showing the relationship between the table references according to the fourth embodiment of the present invention. It is a figure explaining how the table is referred and what kind of table is necessary in each phase. The table reference method is defined as trying to answer a request to various information processing systems while referring to a table. In the first phase, in response to the inquiry, what kind of extraction conditions, classification conditions, and aggregation rules are used to process the trading data to create the target trading data, and various conditions (conditions for creating the target trading data). The purpose is to increase the number of questions that can be answered in various inquiries by creating and managing the relationship table of. If it has already appeared, refer to it, and if it is new, record the new correspondence in the table. In the second phase, the table reference method used to select the evaluation index includes the table used to change the scoring and weighting used to select the most important evaluation index (see the evaluation index selection process). .. It also includes a simpler method of selecting an evaluation index from the words of the inquiry. In the third phase, the operation is decided by referring to the association table of which operation step is taken and what result set is returned for the task through the operation-related table. In the 4th phase, the display method selection table is defined as a table that associates the result set with what kind of expression method to take, whether it is a graph, table, chart, which item should be the X-axis, and so on. The table reference method is defined as determining the next process in the information processing system by referring to these tables.

FIG. 94 is a diagram showing an input form method (transaction data) according to the fourth embodiment of the present invention.

It is a figure which showed an example of the format which a user, an administrator, etc. input a buying and selling data from a form. In the case of a new purchase, a screen for inputting four items (or more) is presented as shown in the above figure. On the other hand, if you press the sell button of the stocks you own, a list of stocks you own will be displayed, and as shown in the figure below, the items to be entered are limited to the stock price to be sold and the date of sale, and the decision to sell can be easily made to the information processing system. Refers to the mechanism for sending. The quantity is a pull-down method and includes a means for reducing the unit with respect to the number of shares held. (For example, if the number of unit shares of FANUC is 100 shares and 500 shares are held, 500 shares, 400 shares, 300 shares, 200 shares and 100 shares are displayed in a pull-down method, and the quantity to be sold is selected). The contents of these input forms are sent to the information processing system to show that various trading data are updated.

FIG. 95 is a detailed first phase diagram of AI learning according to the fourth embodiment of the present invention.

It is a figure which shows concretely how the AI learning of the 1st phase of FIG. 92 is performed. Decide what kind of trading data to create for the inquiry data. When the inquiry content is known (that is, there is a matching inquiry in the condition table), the condition is determined, the extraction condition and the like are determined, the condition is instructed to the information processing system, and trading data is created. On the other hand, if it is unknown, the guessing program runs, analyzes the inquiry data, and learns under what conditions the trading data should be extracted (or classified, aggregated, processed) while referring to the teacher data. go. Examples of teacher data include tables created by the reference table method. Let the program remember the determination of the conditions, and for the word 2020, we will measure the improvement of verification and forecast results while learning the association such as creating the trading data to be aggregated for each period in 2020.

FIG. 96 is a detailed second phase diagram of AI learning according to the fourth embodiment of the present invention. FIG. 96 is a diagram specifically showing how the AI learning of the second phase of FIG. 92 is performed. For the evaluation indexes derived from the inquiry data and the trading data created in the first phase, we will decide which evaluation index should be the important evaluation index. If the inquiry content is known (that is, there is a matching inquiry in the evaluation index selection table), a key performance indicator is determined, the evaluation index is instructed to the information processing system, and the evaluation index is the next operation step. It is utilized in. On the other hand, if it is unknown, the guessing program runs, analyzes the inquiry data and the derived evaluation index, and refers to the teacher data to determine which evaluation index is important and which evaluation index should be used as the important evaluation index. I will learn. Examples of the teacher data include tables created by the reference table method. Make the program remember the determination of the most important evaluation index, and measure the improvement of verification and forecast results while learning the association such as creating the average trading profit / loss ratio with the trading profit / loss level trading data in the term trading profit / loss ratio. To go.

FIG. 97 is a detailed third phase diagram of AI learning according to the fourth embodiment of the present invention. FIG. 97 is a diagram specifically showing how the AI learning of the third phase of FIG. 92 is performed. From the inquiry data, decide which operation to perform in the operation determination table. When the inquiry content is known (that is, there is a matching inquiry in the operation determination table), the operation is determined and the operation is instructed to the information processing system. On the other hand, if it is unknown, the guessing program runs, analyzes the inquiry data, and learns which operation step should be taken while referring to the teacher data. Examples of the teacher data include tables created by the reference table method. We will make the program remember the decision of the action, and measure the improvement of the verification and the prediction result while learning the association such as creating ranking data for the words ranking and ranking. Further, once the operation is decided, what kind of generated data is to be generated is determined in the generated data determination table together with the most important evaluation index determined in the second step. For example, in response to the question of the trading profit / loss ratio in 2020, the trading profit / loss ratio may be determined and used as generated data to be transmitted to the next step. If it is known or unknown, the process is similar to that of determining the operation.

FIG. 98 is a detailed diagram of AI learning according to the fourth embodiment of the present invention, and is a fourth phase diagram. FIG. 98 is a diagram specifically showing how the AI learning of the fourth phase of FIG. 92 is performed. Generated data generated in the third phase Decide which display method to select. If the contents of the result set are known (ie, there is matching generated data in the display method table), the display method is determined and displayed. On the other hand, if it is unknown, the guessing program runs, analyzes the generated data, and learns which display method is optimal and which display method should be selected with reference to the teacher data. Examples of the teacher data include tables created by the reference table method. Make the program remember the decision of the display method according to the generated data, and learn to select the column graph by the display method to compare the most important evaluation index between Mr. A and the average value, and verify and predict the result. Measure the improvement.

FIG. 99 is a table of data to be aggregated by period according to the fourth embodiment of the present invention. Three typical examples of creating trading data subject to aggregation by period are compared with the profit and loss that can be calculated, the processing method, the calculation method, what can be done, and so on. By the way, the period comparison such as the transition of the valuation amount, which is common in securities companies, is the valuation amount version, and the pseudo version is a technology that goes one step further. Comparing the full version and the pseudo version, the total profit and loss that can be calculated by the pseudo version can be determined for each period. For example, if the valuation amount at time A is 10 million yen and the valuation amount at time B is 12 million yen, it can be understood that the period profit / loss during the AB period has increased by 2 million yen, but when it comes to the breakdown of trading profit / loss and unrealized profit / loss. , Even the total numbers are inconsistent. This is because during the AB period, there are many exchanges between trading profit and loss and unrealized profit and loss, such as from holding to selling and from purchasing to holding. For example, in the case where the A issue is sold during the AB period, assuming a case where the purchase is 1000 yen before the A period, the stock price at the time of A is 1200 yen, and the stock price at the time of sale is 1500 yen, the unrealized gain at the time of A is 200 yen. (1200-1000) becomes 500 yen (1500-1000) in trading profit / loss at the time of B, but the actual period profit / loss must be revalued to 300 yen (1500-1200) in trading profit / loss. Does not come out. It is the complete version that can fully implement these.

FIG. 100 is a summary view of FIGS. 24 to 26 according to the fourth embodiment of the present invention. In the case where the time A is January 9, 2019 and the time B is February 3, 2020, the case where the upper row was purchased before the time A was reassessed. Cases after point A indicate that revaluation is not necessary, cases sold by point B, upper part is a case purchased before point A, and revaluation to time point A is required, but lower part is not necessary. It is a figure which showed that.

FIG. 101 is an explanatory diagram of the first phase according to the fourth embodiment of the present invention. In the phase of determining the trading data set to be the target of the first phase, conditions such as extraction conditions, classification conditions, and aggregation rules are determined from the trading data, the trading data to be aggregated is created, and the components of the trading data are used as the reference. A diagram showing that the target trading data set is created by creating the component trading data under various conditions and creating the profit / loss level trading data depending on the level at which the target profit / loss level is set. Is.

FIG. 102 is an explanatory diagram of the second to fourth phases according to the fourth embodiment of the present invention. In the second phase, based on the target trading data set created in the first phase, the evaluation index is calculated, selected, and displayed, and then the evaluation index is used to display the evaluation index, which is an operation step. It is a figure explaining a series of flow of generating evaluation, comparison, ranking, diagnosis, and advice data in the information processing system, and displaying them to a user, an administrator, and the like. 101 and 102 are a system diagram and an overall picture of the information processing system.

FIG. 103 is a verification chart diagram of brand selection according to the fourth embodiment of the present invention. It is a verification chart of stock selection and is used to evaluate the holding status from the actual purchase date to the present. You can see at a glance the trends of other stocks during the holding period, and verify whether the purchase on the purchase date was the correct answer among the many choices. It is a chart that can verify what was the case with a better selection, what was the case with the average, etc., and can display a list of comparison results with other stocks.

FIG. 104 is a verification chart diagram of a brand purchase time according to the fourth embodiment of the present invention. It is a verification chart of the purchase time of a brand, and is used to evaluate the holding status from the actual purchase date to the present. At a glance, you can see the trends of other investors during the holding period, and from the purchase on the purchase date, you are forced to decide whether to hold or sell every day. It is possible to verify what the investors who bought the same stock on the same day were doing. It is a chart that can verify what was the case with a better choice, what was the case with the average, etc., and can display a list of comparison results with other investors.

FIG. 105 is a stock investment trend chart of another investor during the holding period according to the fourth embodiment of the present invention. It is a chart showing the trend of stock investment by other investors during the holding period, and is a chart showing whether the stock has been bought and sold in the same period from the actual purchase date to the present. You can see at a glance the trends of other investors during the holding period, and you can verify what kind of behavior the investors who purchased the same stock during the period were doing. It is a chart that can verify what was the case with a better choice, what was the case with the average, etc., and can display a list of comparison results with other investors. FIG. 104 is a chart for checking the trends of investors who purchased the same stock on the same purchase date, but this chart is a chart for checking how other investors have moved during the holding period of the same stock.

FIG. 106 is a stock investment trend chart 2 of another investor during the holding period according to the fourth embodiment of the present invention. Similar to Fig. 105, it is a chart showing trends in stock investment by other investors during the holding period, and how other investors bought and sold the stock during the period from the actual purchase date to the present. It is a chart that you can understand. You can see at a glance the trends of other investors during the holding period, and you can verify what kind of behavior the investors who purchased the same stock during the period were doing. It is a chart that can verify what was the case with a better choice, what was the case with the average, etc., and can display a list of comparison results with other investors. FIG. 104 is a chart for checking the trends of investors who purchased the same stock on the same purchase date, but this chart is a chart for checking how other investors have moved during the holding period of the same stock. The viewpoint is different from that of FIG. 105.

FIG. 107 is a diagram illustrating three methods of calculating an evaluation index according to the fourth embodiment of the present invention. In the step of calculating the evaluation index from the profit / loss level trading data created up to the fourth step, there are three methods, and it is a diagram illustrating the three methods in a diagram. The more to the right, the more evaluation indexes appear, and detailed evaluation indexes can be calculated.

FIG. 108 is an explanatory diagram of a composite table of purchase data and sale data according to the fourth embodiment of the present invention. In the first step, if possible, it is one of the processes of processing and shaping information such as trading data obtained from a securities company in the process to be introduced to make trading data easy to handle. It is a figure which shows the method of importing the sale data into the purchase data once divided into purchase data and sale data. There are many other ways to do this, but it is important to combine the buying and selling into one line.

FIG. 109 is a leverage effect and compound interest effect diagram according to the fourth embodiment of the present invention. This is an example of displaying a graph of specific examples taken up in the linked holding status evaluation.

FIG. 88 is a notation diagram of the interlocking possession status evaluation according to the fourth embodiment of the present invention. It is a table of specific examples explained in the section of linked unrealized profit / loss level trading data.

FIG. 110 is an explanatory diagram of a plurality of methods for calculating an evaluation index according to the fourth embodiment of the present invention. There are various ways to calculate the evaluation index, such as investment target by period, investment target, investor, evaluation index by transaction data, corporate performance. It is a diagram showing that various targets can be evaluated, compared, ranked, diagnosed, advised, etc. by using an evaluation index calculated from a technical index value or a combination thereof.

FIG. 111 is a calculation table diagram of an evaluation index according to the fourth embodiment of the present invention. It is a figure of a table that manages what kind of procedure is used to calculate the evaluation index, and conversely, what kind of procedure is required to calculate the evaluation index, and a performance forecast table that is managed by another table.

(First step)
The first step is a step of acquiring trading data and the like, and is a step of acquiring trading data including transaction data from a securities company, a user, an administrator, and the like. Normally, the trading data collected here is targeted for the next processing. Of course, in the case of a trading agency such as a securities company, this acquisition step may be few. Data associated with trading data includes technical indicators, tables such as stock price data, and stock information. It may include a phase of processing into a certain format. It may include a display phase. It may include an AI (machine learning, intelligent calculation, etc.) phase.

(Definition of trading data)
Trading data includes trading data, which is trading data in a narrow sense, and trading data in a broad sense, which is data that can be linked to trading data in addition to trading data, such as market data, processing data, rights data, and input data. can give.

The transaction data is based on the type of investment product, the purchase date of the investment product, the purchase price of the investment product, the purchase quantity of the investment product, the sale date of the investment product, the sale price of the investment product, the sale quantity of the investment product, etc. It is data that is decided, and is trading data in a narrow sense.

There are trading data in which profits and losses are fixed and trading data in which profits and losses are not fixed. Trading data for which profit or loss is not fixed is usually entered with a market price or a point-in-time price in order to calculate unrealized gains and losses. Both are included in transaction data (trading data in a narrow sense), but there are cases where processing is required. Such processing is applied when making a certain format. This processing may be performed at the time of creating the trading data to be aggregated, or may be performed at the time of obtaining the trading data.

Data associated with trading data (trading data in a broad sense) includes market data, processing data, rights data, input data, and other table data.

Market data includes market prices and exchange rates of investment products, rights data includes rights data associated with holding investment products (dividends, stock splits, etc.), and processing data includes purchases of investment products. Price (purchase unit price x purchase quantity), sale price, sale profit / loss, total value, average value, maximum value, minimum value, etc. are raised, holding quantity x market price = market price of owned products, sale date of investment products- Purchase date of investment product = holding period, etc. Processing data refers to data calculated by processing from acquired data. Input data refers to the data entered by the user or administrator in the input form. The input data includes, for example, input data to be input in a field for inputting a reference medium, a reference technical index, or the like when a user inputs transaction data. The input data also includes input data in which the administrator inputs data associated with the transaction data in the input form (for example, a securities company, an advisory company, a course name, an investor code, a technical index value at the time of transaction execution, etc.).

Other table data is used for data that is easier to manage if it is managed in a separate table. Other table data includes, for example, an investment target table, an investor table, a performance upward revision table, a technical indicator table, an investment type table, and the like. It is possible to prepare a separate table that includes the same items as the trading data items, link them with common items, and include the information managed in the separate table in the items of the trading data to be aggregated.

Then, it can be used as an extraction condition or as a component (component trading data), and various uses can be expected. Items related to the items in the trading data will be managed, and the trading data will be broader, manageable, and more understandable. Furthermore, all the data necessary for management are management items of trading data.

(Definition of creating modified trading data table)
Data imported from securities companies is often divided into purchase data and sale data, making it difficult to process afterwards. It is best to insert a process that can be handled in a certain format by creating a modified trading data table.

(Problems of conventional technology)
Trading data becomes very difficult to handle if it is imported in different formats for each securities company. By formatting to a certain format, all trading data can be put together in one format.

(Action of creating modified trading data table)
In many cases, the purchase data and the sale data of the trading data are combined. In that case, it is best to put together the format by making a table in which purchase and sale are combined in one line through the process of creating the composite table of FIG. 108 (first step). As a result, the trading profit and loss can be calculated immediately. The next process is the handling of purchase data in which purchase data and sale data are not linked. In the first process, there is purchase data that is not linked to the sale data, and this becomes unopposed trading data. By creating a table in which the unreversed trading data exists in one table, the counter-trading data has the purchase price, the selling price, and the market price, and the unreversed trading data has the purchase price and the market price. A modified trading data table is created.

(Effect of creating modified trading data table)
After going through this process, the total profit / loss can be calculated immediately by the information processing system, and there is an effect that the trading profit / loss or the unrealized profit / loss can be easily derived for each purchase data.

(Specific example of creating a modified trading data table)
The format is different for each securities company, but it is modified by the trading data table. The format of the modified trading data table can be completed by making the table include at least the profit and loss (in the case of counter-trading, the trading profit and loss, and in the case of non-counter-trading, the item of unrealized gain and loss may be included).

(Significance of correction of acquired data (non-opposite trading data))
The data imported from the securities company goes through the process of creating a composite table of purchase data and sale data (Fig. 108) (first step), imports market value valuation (second step), and includes counter-trading data and non-counter-trading data. A table is created in which the counter-trading data has a purchase price, a selling price, and a market price, and the non-counter-selling data has a purchase price and a market price.

As shown in the identification of unreversed trading data, the market value evaluation process (Fig. 85), and the method of capturing investment product prices (Fig. 86), the stock price table linkage method in Fig. 86 is the best, and as shown in Fig. 85, unreversed trading data. The market value, date, and market value are added to, and if similar items are added to the counter-trading data, they will be utilized in later processes. At this time, if the purchase data and the sale data are separated, it is best to insert a process of combining them with the trading data.

Unreversed trading data (unrealized profit / loss level trading data in the subsequent process) refers to investment products that are still in possession (or are being sold if they come from selling). Unreversed trading data is trading data whose profit and loss has not yet been determined, and is trading data in which the valuation price changes daily depending on market price trends, and requires processing different from the confirmed trading data. However, if you include this market price in the traded data, it will be useful in a later process, so it is good to include it (necessary in the 4th step of the profit and loss level trading data).

(Issues to correct acquired data (unreversed trading data))
The valuation amount of unreversed trading data changes according to the holding quantity, but it is necessary to evaluate by the holding quantity x the market price of the investment product. One of the correction processes of acquired data. In addition, the stock price transition after the sale is also included in the trading data, and it is possible to grasp what would have happened if the stock had not been sold.

(Action of correction of acquired data (unreversed trading data))
Correction is possible by creating a table that includes the date and time at time A and the market price at time A as a minimum, or by including these two items in the items of trading data. It does not matter whether this process is performed in the acquisition step of the first step, the creation step of the trading data to be aggregated, or the creation step of the profit / loss level trading data. The same applies to the counter-trading data, which may be linked with the stock price data table or included in the trading data item. However, considering the cooperation later, it is better to cooperate in another table.

(Effect of correction of acquired data (non-reverse trading data))
By adding the correction process, it becomes possible to know the holding status of unopposed trading data, and there is an effect that the holding status can be known even in the process of creating trading data. By being able to capture trends after conducting counter-trading in this process, it will be possible to grasp in detail whether or not the sale was the correct answer at the fourth level of the profit and loss level trading data.

(Specific example of correction of acquired data (unreversed trading data))
(Specific example 1 performed in the acquisition step)
Since it is performed using the trading data that is the basis before creating the trading data to be aggregated, the processes after the second step become easier to understand.

(Specific example 2 performed in the acquisition step)
When performing in the process of creating trading data to be aggregated, add the date and time (including date) and market price items in the additional items of trading data. Here, it may be added to the traded data. In addition, by linking with the stock price data table, time-series data can be easily linked, and the market price after sale and the stock price sold can be easily compared.

(Specific example 3 of correction of acquired data (unreversed trading data))
Profit and loss level You may do it in the step of creating trading data. There is a fourth level in the creation of this profit / loss level trading data, and since the market price after sale is used here, an item may be added to the trading data or it may be imported from the table.

What kind of decision can be made by making it possible to add various things such as adding media, adding securities companies, adding charts, adding technical indicators, adding upward revisions to business performance, etc. to the trading data at the time of purchase or sale. There is an effect that it is possible to follow up whether the sale is successful. Component It becomes one component of the trading data, and it is possible to extract data such as by medium from the trading data to be aggregated. It will be very useful in the later process.

The purpose of increasing the data linked to trading data is to improve the ability of users to give advice on investment methods for investment products, to hide hints for solving various investment issues, and to provide useful information for investors. This is because it can contribute.

(Significance of adding acquired data (input data))
The database is expanded by adding input data to the transaction data. For example, if the brand purchased on February 2 is purchased based on the quarterly report, the reference medium may be the quarterly report, and if the adviser is company A, the advisor item may be company A.

It may include a case entered by the administrator. For example, market data such as a technical indicator RSI of 20% at the time of purchase of a stock may be input. It may be automatically entered in the market data. By importing related data related to such transactions into the database, various effects are produced. In the first place, the trading data to be aggregated by investment target is included for this purpose, and it is understood that the multi-layered ranking and the component comparison process cannot be understood from the transaction data alone because of this link. be. By adding input data, it becomes even stronger.

(Additional issues of acquired data (input data))
The original data of a securities company is difficult to understand and use. By increasing or processing additional items, the added value of data will increase, and the information that users can understand will increase.

(Additional action of acquired data (input data))
The unrealized profit / loss trading data or the trading profit / loss trading data may be displayed, and an item may be added to the purchase data or the sale data. Additional items may be displayed and entered when entering transaction data. The administrator may enter it later. For example, the technical index of the purchase date of the corresponding purchase brand can be easily verified later and input or uploaded as additional information.

By adding items such as the securities company that bought and sold, the advice company that was used to buy and sell, the medium, etc., the added value of the data will increase, and it will be more effective to understand more.

(Additional effect of acquired data (input data))
The additional data at the time of purchase or sale becomes a component of the component trading data, and has the effect of being able to be used as a reference for the trading data to be aggregated. The effect of this is that data can be extracted and aggregated for each aggregation target and each component.

(Specific example of adding acquired data (input data))
For example, if you add a reference medium, you can expect the effect of being able to verify later which medium was used for the most successful buying and selling.

Usually, the data at the time of the transaction includes the execution date, the price of the execution, and the quantity of the execution at a minimum. In order to find out the cause of the event at this time, a great effect can be expected if the technical index values, reference media, corporate events, etc. at that time are stored in a database.

(Specific example 1)
Enter the technical index value. The data item must include the technical index value of the issue at the time of purchase or sale, including whether it is entered by the user or the administrator in the form, automatically imported or automatically calculated. Means.

In this case, for example, it is possible to compare the trading data of the trading data purchased with the technical index value of RSI of 20% or less and sold at 80% or more with the trading profit / loss ratio of the entire trading data.

What kind of decision can be made by making it possible to add various things such as adding media, adding securities companies, adding charts, adding technical indicators, adding upward revisions to business performance, etc. to the trading data at the time of purchase or sale. There is an effect that it is possible to follow up whether the sale is successful. Component It becomes one component of the trading data, and it is possible to extract data such as by medium from the trading data to be aggregated. It will be very useful in the later process.

(Method of improving the acquisition frequency of trading data)
(Issues of acquisition frequency of trading data)
Unlike market data and rights data, transaction data of investment products (trading data in a narrow sense) is updated at different frequencies depending on the user. Scalping and day traders, who trade daily, trade frequently, so the frequency is high, and it is not uncommon for salted investors to rarely trade once a year. The frequency of transactions varies from person to person, and real-time performance is not always required of everyone. On the other hand, market data is required to be real-time, such as the prices and exchange rates of investment products held, and there is a wide range of needs for frequency, such as real-time, 30-minute delay, once a day, once a week, and so on. Such market data is relatively easy to obtain. On the other hand, transaction data is required to have a means for the person who made the transaction to update it in some way.

(Effect of acquisition frequency of trading data)
For example, the transaction data of a person who made a transaction at a securities company changes in real time. As mentioned above, there are several methods for how often and how to capture this transaction data, and each has its advantages and disadvantages. You may choose the frequency and method according to the transaction frequency.

For example, in the case of day trading with high frequency, if possible, it is suitable to capture data by API linkage or scraping method. For users who trade infrequently and on average about once a month, it is sufficient to import market data such as stock prices more frequently and to import transaction data once a month. Is. In this case, it can be said that the CSV download / upload method or input using the input form is suitable.

In this way, the method of importing trading data (trading data in a narrow sense = transaction data) and the method of changing the import frequency according to the transaction frequency are useful and realistic methods.

(Effect of acquisition frequency of trading data)
By changing the import method and frequency according to the transaction frequency, we will balance security and convenience, and by deciding, we will consider both the convenience of the customer and the security risk associated with increasing the frequency. The effect of fulfilling can be demonstrated.

(Specific example of acquisition frequency of trading data)
For users who have transactions more than once a day, we will proceed with the update procedure of API and scraping method, and for users who have less frequency than once a month, we will promote input in the input form. Can be given.

The following methods can be considered as the input form method.

(Significance of form input method (transaction data version))
As mentioned earlier, updating transaction data depends on the degree of security and transaction frequency. This form input method (transaction data version) is recommended for users who do not frequently trade.

(Problems of the conventional method)
Downloading and uploading CSV is quite a hurdle for the elderly and those who are not accustomed to operating a computer.

(Action of form input method (transaction data version))
As shown in FIG. 94, there are a purchase button and a sell button. When the purchase button is pressed, a purchase form appears, and when the sell button is pressed, a list of owned stocks appears. Since it is linked to trading data, it is possible to pull the list of stocks held from the unrealized profit / loss level trading data. The quantity, brand code, etc. have already been entered, and the user can record the transaction that Company F sold for 20000 yen to 1/1. All the user records is the price, date and check, and transaction data can be entered. Further, this data is transmitted to the storage unit 33, disappears from the unrealized profit / loss level trading data, is updated to the trading profit / loss level trading data, and the record can be confirmed later.

(Effect of form input method (transaction data version))
For day traders who trade many times a day, this method is difficult, but for normal level trading, you can enter it at any time you like, and once you enter it, your data will be updated immediately. You can expect a special effect that you can experience the ranking fluctuating depending on the situation.

After acquiring these trading data, the process of creating the trading data to be aggregated is performed.

The first step is the step of creating trading data. The second step is the step of creating the trading data to be aggregated (this step). The third step is a step of creating trading data for each component (even after the fourth step). The fourth step is the step of creating profit / loss level trading data (even after the second step). The fifth step is the calculation step of the evaluation index.

From the second step to the fourth step, the original trading data is narrowed down by creating the trading data to be aggregated, the component trading data, and the profit / loss level trading data, and the target trading data is determined in the evaluation index calculation step. Is. FIG. 101 shows a schematic diagram. Explaining this process with reference to FIG. 76, first, in the step of S899, it is instructed whether the information processing system extracts, classifies, aggregates, and decides how to do it. For example, if the condition is "extraction condition: investment target = stock", the information processing system extracts only the stock trading data (aggregation target trading data by investment target).

If the condition is "extraction condition: brand code = 6701", the information processing system extracts only the trading data whose brand code is 6701. If the condition is "extraction condition: investor = A", the information processing system extracts only the trading data of Mr. A (the trading data to be aggregated by investor). "Extraction conditions: (Unreversed trading data as of January 1, 2020 (purchase in possession (or sale if entering from sale) data) and / or purchase date and / or sale date are both 2020 Under the condition of "extracting trading data (from January 1st to December 31st)", the information processing system extracts the trading data for 2020 (trading data subject to aggregation by period).

In the case of trading data subject to aggregation by period, it is necessary to include trading data that was held without buying or selling in 2020, and for the amount that was held, it is necessary to calculate only the amount that increased or decreased in 2020. be. Under the above conditions, such trading data is included and profit / loss is adjusted, so that the trading data is more elaborate for each period. In the creation of the trading data to be aggregated, there are determination of extraction conditions, determination of classification conditions, determination of aggregation rules, and the like.

In determining the classification conditions, if the classification and aggregation conditions are "investment target products = classification aggregation criteria", for example, if the investment target products include stocks, virtual currency, and FX, they are aggregated by investment target for each category. Multiple trading data to be aggregated are created.

From here, it is also possible to set the extraction condition to "investment target is stocks". If the classification aggregation standard is "investor type = classification aggregation standard", a plurality of trading data aggregated separately such as day trading type and swing trading type included in the investor type can be created. When the classification standard is "investor type = classification standard", multiple investment type-specific trading data to be aggregated are created in the same way, but those trading data are not aggregated and the trading table is only classified. ..

After the creation of the aggregation target trading data, the extraction condition, the classification condition, and the aggregation condition of the component trading data are determined, and the component trading data is created.

(Steps S901 and S902) Extraction conditions, classification conditions, based on the components included in the trading data to be aggregated (generally, management items on the database (including cases linked in another table)) Aggregation conditions are determined.

For example, the type of industry of a brand that is one of the components of the trading data for each investment target, which is a collection of only stock trading data (extraction condition: investment target = stock), is classified and aggregated (component classification and aggregation standard =). (Industry of issue), based on the trading data to be aggregated of stocks, classification is performed for each industry of issue, and aggregated component trading data is created.

Data such as the total purchase price and the total sales price of brands whose industry is electricity are aggregated.

For example, if you create component trading data with the trading data to be aggregated as "extraction condition: investment type = day trading type" and "component extraction condition: stock type = trader stock", the trading performed by a day trading type person Of these, only the trading data bought and sold by the trading stock is extracted.

The component trading data is the same as the trading data to be aggregated in that, in addition to the classification aggregation standard, there is also a simple classification standard that does not aggregate.

When this configuration trading data is created, it becomes the next step of creating profit / loss level trading data.

The next step is to determine the target profit and loss. The ultimate purpose of buying and selling is to improve profit and loss. There are several levels of profit and loss such as total profit and loss, trading profit and loss, unrealized profit and loss, winning profit and losing loss, and it is a step to decide which profit and loss should be targeted for improvement.

If the trading data meets the conditions of the above-mentioned day trading type trading data, it is good to decide the trading profit / loss as the target profit / loss, or in the trading data subject to aggregation by investor, the total profit / loss that can judge the overall ability is It depends on the nature of the trading data created so far.

If the target profit / loss is trading profit / loss, the trading profit / loss level trading data is created from the aggregated trading data or component trading data created so far (it may be held in the previous process). The trading data created in this process is the trading profit / loss level of (extraction condition: investment type = day trading type) and (component extraction condition: stock type = trading stock). Only trading profit / loss data that has been traded and whose profit / loss is fixed is collected.

This will be the trading data for the work that will be the basis for the next step. In all of these processes, various extraction conditions, classification conditions, classification aggregation conditions, created trading data, management items, components, final trading data, and the like are stored in the storage unit 33.

(Step to create trading data to be aggregated)
The steps for creating the trading data to be aggregated may be created manually or automated.

(Creation of trading data to be aggregated)
When creating the trading data to be aggregated, the information generation unit 3021 determines the trading data to be aggregated by period, the trading data to be aggregated by investor, and the investment target, depending on what criteria and what the acquired trading data is evaluated. Create trading data to be aggregated by profit or loss, or trading data to be aggregated by profit or loss. Then, even if the information generation unit 3021 creates, for example, the aggregation target trading data of Mr. A in 2019, the aggregation target trading data of Mr. A's B brand, etc. by combining and editing each aggregation target trading data. good. Then, the information generation unit 3021 can also collectively create a plurality of disparate aggregated trading data. For example, the aggregated trading data of Mr. A's A securities company, the aggregated trading data of Mr. B's B securities company, and the aggregated trading data of Mr. C's C securities company are combined into one and the aggregated trading data. It is also possible to create data and classify it according to criteria such as period to create new aggregated trading data. For example, it is possible to create a new aggregated trading data by combining the aggregated trading data of Mr. A's A securities company, B securities company, and C securities company.

In this case, investor and securities company data are also included in the database items to help later classification. For example, in the former case described above, the aggregated trading data of Mr. A's securities company A can be easily processed in various ways by adding the data of investor A and securities company A. The input data may be prepared from the beginning, may be added later, or may be input by a user or an administrator. The input data may be created in the first step, or may be added in the second step, the third step, or the fourth step.

If trading data that has not been traded in the opposite direction is included, it may include a processing process for inputting the current price and the market price of the investment target at the time of evaluation. Further, processing such as calculation of the total value and calculation of the average value may be included. Processing that is easy to handle may be included in the third and subsequent steps.

(Step to create trading data to be aggregated)
(Significance of creating trading data to be aggregated)
The aggregated trading data of Mr. A's A securities company (for example, the aggregated trading data called aa1) is imported into the database in the trading data acquisition step. The aggregated trading data of Mr. B's A securities company (for example, the aggregated trading data called ba1) is imported into the database in the trading data acquisition step. By continuing this, the aggregated trading data to be aggregated (for example, the aggregated trading data called A1) is created. By classifying, extracting, and aggregating this base trading data to be aggregated based on criteria (period, investor, investment target, etc.), the trading data to be aggregated (for example, A1-K, which is the target of aggregation by period) Trading data) is possible.

It is possible to use trading data at the trading profit / loss level, trading data at the total profit / loss level, or trading data at the unrealized profit / loss level. .. In addition, input data, rights data, processing data, separate table data, etc. other than trading data obtained from a securities company may or may not be included. This is the same for the first step and the third and subsequent steps.

The aggregated trading data to be aggregated may or may not be extracted under certain conditions, and may or may not be aggregated. It may or may not be classified. It may or may not be aggregated (including calculation of total and average value, determination of maximum value, etc.). Based on this aggregated trading data, we will take steps after the second step.

(Issues for creating trading data to be aggregated)
Trading data plays an important role in the target part of "what" of what, how, classification, evaluation, ranking, comparison, diagnosis, and advice. By taking the steps to create the target trading data, the work target (the target of the first stage of processing, extraction, and classification) is determined, and various trading data can be handled.

(Action of creating trading data to be aggregated)
How you decide on a target depends on what you want to do. For example, if you want to create a ranking of the total profit and loss of investors in 2020, create the trading data to be aggregated in 2020 with the trading data to be aggregated by period. By creating total profit / loss level trading data for each investor by component (even if you have it in the previous process), you can create trading data that will be the basis for creating rankings. This is possible because trading data is created for each investor, in which the total profit and loss value for 2020 is calculated. Once the what you want to do is decided, the trading data to be aggregated is decided, so the administrator may decide what you want to do, or the user may decide. You can choose either from a questionnaire or a list to decide what you want to do, you can automate it and ask for an answer, or you can decide each time.

If you want to create a ranking of the total profit and loss of investors in 2020 as described above, the purpose of this step is to create trading data to be aggregated by period in 2020. The creation of trading data subject to aggregation by period will be described later.

(Effect of creating trading data to be aggregated)
After going through the process of creating not only the trading data to be aggregated by Mr. A's A securities company, but also the trading data to be aggregated including Mr. A, Mr. B, and Mr. C, the components such as by investor, investment target, and period. By creating separate trading data, ranking and comparison can be facilitated, and a wide range of evaluation, ranking, comparison, diagnosis, advice, etc. can be performed.

(Specific example of creating trading data to be aggregated)
(Specific example 1)
When issuing a comprehensive profit / loss ratio ranking for investors in FY2020, the information processing system summarizes the trading data to be aggregated by period for all investors in FY2020, creates component trading data for each investor, and for each investor. By creating comprehensive profit / loss trading data based on the component trading data for each investor and calculating the total profit / loss ratio, which is one of the evaluation indicators that make up the total profit / loss, for each investor. Data on the total profit / loss ratio for FY2020 will be available. By ranking the total profit / loss ratio for each investor based on the total profit / loss ratio, the total profit / loss ratio ranking for 2020 of the investor can be created.

Investors are displayed anonymously, and the display step is to create a table called ranking in the first column, investor name (anonymous) in the second column, and total profit / loss ratio in the third column.

(Specific example 2)
When comparing each index of the average value of investor A and the whole investor, the information processing system summarizes the trading data to be aggregated by the investor, creates the component trading data of investor A and the whole investor, and creates the trading data. By creating trading data below the total profit / loss level and calculating the evaluation index that constitutes the total profit / loss, the evaluation index of investor A and the evaluation index that is the average value of the whole are calculated. Now you have the basic data.

By showing the important evaluation index on the radar chart and showing the average value of Mr. A's evaluation index and the overall evaluation index on the radar chart, the average value of investor A and the investor can be compared at a glance. Utilizing this, it is possible to provide diagnosis and advice.

(Specific example 3)
In order to clarify the degree of contribution of a stock to the trading profit, the information processing system creates trading data to be aggregated for all investors, creates component trading data for each stock, and makes a profit composition ratio for each stock. Create items, create trading profit trading data, and calculate the average trading profit ratio, trading profit amount, and total trading profit amount, which are evaluation indexes, for each issue. Now you have the basic data. By setting the total trading profit to 100% of the pie chart and displaying the trading profit amount for each issue as a percentage, it is possible to clarify the degree of contribution of the stock to the trading profit.

As in the above specific example, first decide what you want to do, decide which trading data to be aggregated for that purpose, and if it is necessary to further divide the trading data by component, the trading data to be aggregated. It is basic to create from the above and create profit / loss level trading data by the information processing system according to the target profit / loss (or average trading profit / loss ratio (ROI average)). , The target trading data is created. The order in which the trading data for each component and the profit / loss level trading data are created may be changed.

(About trading data subject to aggregation by investment target)
Includes stocks such as company S stocks, investment trusts, stocks such as ETF bull funds, stocks such as FX yen dollars, and virtual currency stocks. In addition, the stocks may be grouped and the aggregation target may be divided into a trader stock group, an excellent stock group, a high dividend stock group, etc., or an index investment trust group, a robot fund group, etc. may be aggregated. Further, products, product groups, etc. may be included in the total. For example, the information generation unit 3021 separates trading data for each aggregation target such as virtual currency, FX, and stocks, and calculates various evaluation indexes. It is also possible to reclassify the aggregated trading data of stocks, the aggregated trading data of virtual currencies, and the aggregated trading data of FX. The purpose of creating these aggregated trading data by investment target is to convey it to a wide range of investors. This is because the buying and selling of the stock group is not successful, so it is intended to change the investment behavior of investors such as buying and selling the excellent stock group. It can be said that the information generated from the trading data to be aggregated by investment target, which gives rise to various news and gives various notices, is the information that triggers a big change in the investment behavior of investors.

(About trading data subject to aggregation by investment type)
Investment types include investment types defined by type-specific diagnosis, such as day trading type, swing trading type, short-term trading type, medium- to long-term holding type, and salted type. The information processing system divides trading data for each investment type, aggregates each, and calculates evaluation indexes for various aggregation targets. The information processing system collects the day training type aggregated trading data, the swing trading type aggregated trading data, and the scalping type aggregated trading data into a short-term trading type aggregated trading data and reclassifies them. And so on.

It can be said that this is also the content that should be communicated to all investors, as is the case with the trading data to be aggregated by investment target. The information processing system generates various kinds of information, but it is only meaningful when it is transmitted to a wide range of people. It can be said that many people are interested in what kind of actions the day trading type people are doing and what they are doing now. When the media handles this information, various impacts will be created.

(Regarding trading data subject to aggregation by adviser)
The information processing system is for each adviser (advice provider) regardless of individual, corporation, or group, such as buying and selling data judged by listening to Mr. A's investment advice and buying and selling data judged based on the investment advice of investment company A. Divide the trading data and aggregate each to calculate the evaluation index of various aggregation targets. The aggregated trading data of Mr. A's advice, the aggregated trading data of Mr. B's advice, and the aggregated trading data of A investment advisory company are grouped together, that is, the trading data made by the advice is grouped and classified. You can also fix it.

(About trading data subject to aggregation by securities company)
The information processing system divides trading data for each securities company that executed trading, such as trading data that executed trading at securities company A and trading data that executed trading at securities company B, and aggregates each of them for various aggregation targets. Calculate the evaluation index of. It is also possible to reclassify the aggregated trading data of A securities company, the aggregated trading data of B securities company, and the aggregated trading data of C securities company.

(About trading data subject to aggregation by medium)
The information processing system aggregates trading data for each medium according to the medium to be referred to. The information processing system refers to trading data that executed trading with reference to Twitter (registered trademark), trading data that executed trading with reference to the quarterly report, trading data that executed trading with reference to business performance, and charts. Divide the trading data for each reference medium that executed the trading, such as the trading data that executed the trading, the trading data that executed the trading with reference to the automatic trading tool A, and aggregated each to calculate the evaluation index of various aggregation targets. do.

It is also possible to reclassify the aggregated trading data performed by referring to Facebook, the trading data subject to aggregation performed by referring to Twitter, and the trading data subject to aggregation performed by referring to the blog. As described in the explanation of aggregated trading data by investment target, this aggregated trading data was created in order to inform many investors what kind of investment behavior investors are taking and what kind of situation they are in. There is. You can also create articles such as how the investment behavior with reference to Twitter was the result.

(About trading data subject to aggregation by investor)
For example, if the target of aggregation is an investor, the information generation unit 3021 may include an individual investor group, an institutional investor group, an individual investor A, an institutional investor B, an investor type group centered on short-term trading, and a medium- to long-term. Investor type of holdings Aggregate trading data by investor type such as group investors. Furthermore, it is possible to classify into various investors by calculating the evaluation index of trading data by the information processing system. For example, by creating an investor group with the top 10 overall profit / loss ratio, an investor group with the top 10 win rate, an investor group with the top 10 unrealized profit ratio, etc., when other investors make a transaction, this investor In the case of a group, it is possible to link data by how to act. It is also possible to reclassify the aggregated trading data of Mr. A, the aggregated trading data of Mr. B, and the aggregated trading data of Mr. C together. It is possible to generate many articles that are likely to be of interest to many people in the trading data to be aggregated by investor. For example, titles such as the investor type group centered on short-term trading vs. the investor group of the medium- to long-term holding investor type group, and which one won in 2020 will be an attractive article. This is one of the significance of creating trading data to be aggregated by investor.

(About trading data subject to aggregation by period)
For example, if the target of aggregation is a period, annual trading data for this one year, monthly data for one month, weekly trading data for one week, daily trading data for one day, and 2019 trading data. It is divided into such things. It is also possible to reclassify the aggregated trading data of 2019, the aggregated trading data of 2020, and the aggregated trading data of 2021 together.

By doing so, it is expected that the generation of articles will be easier, wider, and easier to understand. Unless the period is managed in the database, such data is very difficult to derive. Even if I know the current unrealized gains and losses, even if I compare it with a year ago, I've been buying and selling during that time, and I'm not sure.

Although there are often time-to-period comparisons of portfolios, in most cases they are simply comparing changes in valuations. This is fine if it is the total profit / loss level (that is, the valuation amount level) of the subsequent process, but after the trading profit / loss level, it is very important to create the trading data to be aggregated for each period. The same applies even if the trading data at time A and the trading data at time B remain as time-series data (see FIG. 87).

The reason is how to grasp the complicated situation by period, such as various buying and selling during the AB period, and the holding situation also changing, resulting in unrealized profit and loss and trading profit and loss. The amount of information is significantly different between the mere portfolio transition and the trading data subject to aggregation by period.

The stocks you own, the stocks you have sold, the stocks you bought newly, the stocks you sold immediately, the stocks you still own, etc. are very complicated, and the stock price fluctuates every day. It cannot be derived so easily.

However, this method can be easily derived. The fact that the period is easy to come out means that it is possible to accurately convey the situation that is changing sequentially, which is a very useful method as an article.

For example, you can easily create an article about what is the most profitable stock of the month. One of the purposes of the trading data subject to aggregation by period is to create such current affairs news.

However, even if one of these simple themes is taken, if it is October, the investor who held it on October 1 sold it during October, and the investor who continued to hold it until the end of October. However, if the stock price continues to rise, investors who have been holding until the end of October will have to make a profit in October and receive a higher evaluation than investors who have sold it.

In addition, some investors buy and sell five times in October, making more profit than they keep holding, while losing money at the end of October. It is not so easy to grasp this situation because the stock price, the change in the holding situation, and the trading situation are intricately intertwined. In addition to the period, it is even more so in complicated cases including issues, but there is a special effect that it can be solved by using the trading data subject to aggregation by period.

It seems easy to divide the period in this way, but in the case of trading data, it is very complicated. However, it can be easily derived by creating the trading data to be aggregated by period.

(Definition of trading data subject to aggregation by profit and loss)
The creation of trading data based on profit and loss is usually performed in the fourth step, but sometimes it is better to reconsider the trading data based on profit and loss. In such a case, create trading data to be aggregated by profit and loss. The profit / loss level trading data is aggregated by profit / loss (for example, winning profit), whereas the profit / loss level trading data in the profit / loss level evaluation index is calculated (for example, investor A). , Unrealized loss) refers to the trading data to be extracted and processed.

Since the former is trading data aggregated by winning profit, it is subject to aggregation including the winning profit of Mr. A and the winning profit of Mr. B. On the other hand, in the latter case, since the trading data is narrowed down only to the trading data of the winning profit of the investor A, it is an extraction for evaluating the trading of Mr. A. It is also possible to reclassify the aggregated trading data aggregated by winning profit and the aggregated trading data aggregated by losing loss.

(Step to create trading data to be aggregated)
In the step of creating the aggregation target trading data, the information generation unit 3021 performs the aggregation target trading data by period, the aggregation target trading data by investor, the aggregation target trading data by investment target, the aggregation target trading data by profit and loss, and the aggregation target by investment type. It is divided into trading data, trading data to be aggregated by adviser, trading data to be aggregated by securities company, and trading data to be aggregated by medium. The method of division is determined by the extraction condition, the classification condition, and the aggregation rule (calculation of the average value, total value, etc. by the information processing system). It is also possible to combine these with the aggregated trading data of Mr. A in 2019, the aggregated trading data of Mr. A's brand, and the like. In addition, the trading data to be aggregated is further classified, aggregated, and extracted (including all or all) by period, investor, investment type, medium, securities company, investment target, etc., which are the constituent elements. By subdividing the trading data by doing so, the component trading data is used.

(Relationship with the old method of the trading data creation step to be aggregated)
The old method of understanding the trading data is to collect the trading data in a lump, and in the new method, what kind of target is to be extracted, classified, and aggregated in the new method. Make it clearer.

(Significance of the step for creating trading data to be aggregated)
In the step of creating trading data to be aggregated in the new method, the trading data is extracted by which criteria (investment-specific, investment target-specific, period-specific, etc.), and what classification criteria are used to classify them. Depending on how to aggregate and whether to aggregate (various calculations such as total value and average value) (may or may not include all), what (aggregation target, Mr. A, B brand) The purpose of evaluating (is) is made clearer.

(Issues in the step of creating trading data to be aggregated)
By taking the step of narrowing down the trading data, the evaluation target is clarified, and the evaluation target such as the trading status of company S stock in 2019, the evaluation of the holding status, the evaluation of the trading status of Mr. A, and the purpose are clarified. become. Furthermore, by dividing the aggregated trading data, which is the basis for these, into components such as by period, investor, investment type, medium, securities company, and investment target, and extracting or aggregating them, Furthermore, it becomes possible to know the nature of trading data.

(Action of the trading data creation step to be aggregated)
Decide whether to extract, classify, and aggregate trading data by which criteria (investor-specific, investment target-specific, period-specific, profit / loss-specific, or a combination of them), and use those criteria as the criteria. Create combined trading data. Furthermore, it is possible to create component trading data by dividing the aggregated trading data that serves as these criteria into components such as by period, investor, investment type, medium, securities company, and investment target. ..

(Effect of the trading data creation step to be aggregated)
By executing this step, you can create various trading data such as by period, investment target, profit / loss level, investment type, securities company, adviser, medium, etc., and the evaluation target becomes clear and various. It has the remarkable effect of being able to evaluate various objects from various perspectives. Furthermore, by further dividing the aggregated trading data that serves as these criteria into components such as by period, by investor, by investment type, by medium, by securities company, and by investment target, for example, the investment results of stock A It is also possible to divide by year or by investor, and it is possible to divide the investment results of stocks by brand, by investor, by securities company, and various combinations. Become.

Next, the characteristics of each aggregated trading data will be clarified.

(Definition of trading data subject to aggregation by period)
For example, if the target of aggregation is a period, annual trading data for this one year, monthly data for one month, weekly trading data for one week, daily trading data for one day, and 2019 trading data. It is divided into such things.

FIG. 22 is a diagram for explaining the period-specific aggregation target trading data according to the present embodiment. As shown in FIG. 22, when evaluating the trading status and holding status in a certain period, the valuation amount and cash at the time A are set as the starting point, and as a result of various trading, the valuation amount and cash at the time B are obtained. It will be necessary to evaluate the process.

The trading data required at this time is defined as the trading data to be aggregated by period. FIG. 23 is a diagram showing trading data subject to aggregation by period according to the present embodiment.

For example, if the target trading data for each period is the year 2020, the trading data that was bought and sold from January to December 2020. The data that was bought and sold from January 2020 to December 2020 can be divided into the following.

Data that was held in January 2020 but sold during the period (period data), data that was held in January 2020 but also held in December (period data), 2020 1 The data is purchased from January to December (period data), but the data purchased in November 2019 and sold in December 2019 is not period data. The data bought in January 2021 is not period data either. To define it again, the trading data to be aggregated by period for the year 2020 includes the trading data held in January 2020, the trading data held in one year, and the trading data held in December 2020. There is. There is also the issue of how to handle deposits and withdrawals during the period, but this will be listed separately.

(Old method for trading data subject to aggregation by period)
In the old method, there are explanations such as purchase date and sale date, but there is no explanation for each period. By extracting only the trading data from the time A to the time B, it is possible to accurately grasp the trading and holdings performed during that period. In that case, processing and procedures of trading data are required. Further, in the period comparison of investment results, there is one that shows the transition of the valuation amount between the trading data at the time A and the trading data at the time B.

(Issues of trading data subject to aggregation by period)
In order to accurately evaluate the trading data for a certain period, it is necessary to revalue the trading profit / loss data and the unrealized profit / loss data respectively (or at the same time). This revaluation, procedure, classification of stocks held and trading stocks, and the fact that the stocks held at point A are also related are complicated, which is one of the factors that make it difficult to understand the results of stocks.

As shown in FIG. 23, 1 is the trading data of the investment product purchased by the time A and held at the time B (that is, the amount of increase / decrease due to the continued holding). 2 is the trading data of investment products purchased by the time of A and sold before the time of B (that is, the amount that was previously held but sold during the period). .. Reference numeral 3 is trading data of investment products purchased after the time A and sold before the time B (the portion sold and bought during the period. The period trading profit / loss in a narrow sense). 4 is the trading data of the investment products purchased after the time A and held at the time B (the increase / decrease in the amount newly purchased during the period).

1 and 4 are related to unrealized profit / loss level trading data (products held at the time of B), 2 are related to products that were held but are no longer sold, and 3 is related to trading data at trading profit / loss level (B). Trading profit / loss level at the time of trading Trading data). 1 and 4 show unrealized profit / loss trading data (trading data that is not counter-trading) at time B, and 2 and 3 are trading profit / loss level trading at time B. The method of processing these into trading data subject to aggregation by period is shown below.

The information generation unit 3021 extracts the trading data to be aggregated for each period as a reference (or classifies or aggregates, and may or may not include all) to create the trading data to be aggregated for each period. , Calculate the trading profit / loss level evaluation index or the unrealized profit / loss level evaluation index from the trading data to be aggregated by period, and generate information on the evaluation of the trading status or holding status for each period.

Therefore, if the trading data subject to aggregation by period does not come out in an orderly manner, the profit / loss level trading data, which is a later process, cannot be accurately calculated by the information processing system from the second level onward. In particular, this problem occurs when trying to generate period data from trading data at time A and time B. The method to solve this is the mechanism of evaluation change by the information processing system. In other words, unless the process of trading data subject to aggregation by period is sandwiched, accurate unrealized gains and losses by period and trading profits and losses cannot be calculated even if they can be grasped by total figures. This is because it is necessary to incorporate into the model that it becomes trading profit / loss data or unrealized profit / loss data. This invention has a remarkable effect because it affects all the subsequent processes such as calculation of evaluation index and creation of ranking. However, there is one way to avoid this, which is a method of creating trading profit / loss level trading data first and extracting it for each period, and creating unrealized profit / loss level trading data first and extracting it for each period. These similar technologies will be described later.

Then, when the period is from the time A to the time B, the information generation unit 3021 obtains the trading data of whether the data is held at the time A, held at the time B, or bought / sold within the period AB. By extracting, the trading data to be aggregated for each period is created.

Regarding the trading data of purchased investment products, the standard evaluation value of the investment product is changed from the unit price at the time of purchase to the unit price at the time of A, and among the trading data subject to aggregation by the period, the investment product held at the time of B Regarding the trading data of, the latest closing price of the investment product is changed from the unit price at the time of sale or the current unit price to the unit price at the time B.

FIG. 24 is supplemented. It is a table for calculating the profit and loss of the AB period when the time A is January 9, 2019 and the time B is February 3, 2020. The figures relating to the trading data subject to aggregation by period are from FIG. 24 to FIG. 28, and show the process of revaluation by the information processing system.

First, the information processing system revaluates the unrealized profit / loss level trading data by the information processing system. That is, it is this FIG. 24 that separates 1 and 4 of FIG. 23.

The explanation in the figure below is very complicated, so if we arrange it in relation to FIG. 23, case 1 is the upper part of FIG. 24 (cases that we continued to own), and case 2 is the upper part of FIG. 26 (at the time of A). The case that I had but sold between AB), the case 3 is the case in the middle and lower part of Fig. 26 (the case where the buying and selling was completed within the AB period. The simplest case), and the case 4 is. It is a case in the lower part of FIG. 24 (a case purchased during the AB period and held at the time B) (summarized in FIG. 100).

FIG. 24 is a diagram showing a specific example of the procedure for revaluing the unrealized profit / loss trading data according to the present embodiment. The upper part of FIG. 24 shows the case of FIG. 23. The lower part of FIG. 24 shows the case of FIG. 23-4. (Since the recommended buying date is before point A (here, January 2019), the unit price at point A is used to evaluate the start point, and the latest closing price is point B.)
FIG. 24 shows a procedure for extracting and processing unrealized profit / loss trading data. In the upper case of FIG. 24, the investment target held at the time A needs to be based on the market price at the time A, not the unit purchase price. It is the case of 1 in FIG. 23 that the evaluation needs to be changed.

As shown in the upper table of FIG. 24, the purchase price is 3.93 million yen, the standard evaluation value at time A is 6.71 million yen, and the standard price at time B is 9.33 million yen.

As in the case of 4 in FIG. 23, the investment target that is not held at the time A and is held at the time B may be the purchase unit price.

As shown in the lower table of FIG. 24, the standard evaluation value at the time of purchase and at the time of A is 2.12 million yen, and the standard price at the time of B is 2.77 million yen.

When the upper and lower rows of FIG. 24 are combined, the unrealized profit / loss trading data by period is not the purchase price of 6.06 million yen, but the base price at time A of 8.84 million yen, which is the difference from the base price at time B of 12.11 million yen. 3.27 million yen is the unrealized gain (during the AB period).

Referring to FIG. 24, in the unrealized profit / loss trading data, the valuation amount at time A is 2.12 million yen + 6.71 million yen = 8.84 million yen, and the valuation amount at time B is 9.33 million yen + 2.77 million yen = 12.11 million yen. FIG. 25 is a method of processing trading profit / loss trading data (trading data of counter-trading) into trading data to be aggregated by period.

25 and 26 are diagrams showing an example of changing the trading profit / loss trading data according to the present embodiment into data for each period. In the case of trading profit / loss trading data, there are two stages, FIG. 25 and FIG. 26.

FIG. 25 is an extraction of the trading data that existed within the period from the time A to the time B from the trading data. Specifically, the recommended sell date> time A (January 9, 2019 in this example) and the recommended sell date <time B (February 5, 2020 in this example), that is, the sale. It is an extract of trading data between the time A and the time B. In other words, it refers to trading data whose sale date was between January 9, 2019 and February 5, 2020. Trading data (extracting trading profit / loss trading data) for which trading has already been completed for stocks that are not owned as of February 5, 2020. It is a specific example of the trading data of 2 or 3 of FIG. 23 for each period. In FIG. 25, it is necessary to extract only the trading profit / loss level trading data and then perform the following revaluation processing.

FIG. 26 shows a revaluation of the trading data extracted in FIG. 25. The upper part of FIG. 26 shows the stocks held at the time A but not held at the time B (corresponding to the case 2 in FIG. 23).

When the trading profit / loss (revaluation of the recommended buying date is changed) is calculated by the A time point evaluation, it becomes 2.22 million yen-1880,000 yen = 340,000 yen. In Fig. 26, stocks A and B correspond, and in Fig. 25, stock A had a trading profit of 400,000 yen (trading profit of 404,100 yen from 262,900 yen to 667,000 yen), but it decreased to 210,000 yen in Fig. 26. This is because the recommended buying stock price has been revalued from 2629 yen (February 29, 2016) to the market price of 4480 yen at point A (stock price on January 9, 2019 (point A)). This revaluation is necessary to measure the trading results by period.

The middle and lower rows of FIG. 26 show stocks that are not owned at either time A or time B. In the case of 3 in FIG. 23, the trading data does not need to be reassessed. If the trading profit and loss is calculated as it is, it will be 7.9 million yen-8.14 million yen = -240,000 yen.

This makes it possible to evaluate the trading status, holding status, etc. from the time A to the time B.

However, it goes without saying that by dividing the trading profit / loss level trading data by period, the lower level winning profit level trading data, losing loss level trading data, and lower winning pattern level trading data can be similarly divided by period. stomach. Unrealized P / L level trading data is also divided by period. The top P & L level trading data is similarly divided by period.

It is precisely because the trading data to be aggregated by period is created in this way that it is possible to easily create articles such as the 2020 investor ranking, which affects the subsequent processes. Even if you try to grasp the trading data at the time of A and the trading data at the time of B, you can not proceed to the subsequent process, it seems easy, but it is important to decide how important this process is and whether you can see the profit and loss of the period correctly. Because it is an element, a very large effect can be expected.

(Action of trading data subject to aggregation by period)
In order to evaluate the trading status and holding status from A point to B time, among the holding targets at B time, the investment target held at A time changes the market price information at A time to the purchase unit price and buys / sell data. Remake. All investment targets held at the time of A are re-evaluated from the unit purchase price at the market price at the time of A, and the trading data is created to create the trading data for each period.

The information generation unit 3021 creates the trading data to be aggregated by period from the trading data through the following modifications.

As a method of creation, if the purchase date included in the aggregated trading data is before point A based on the trading data at time B, the record date is set to point A and the purchase (or sale) unit price is the market price at time A. By setting, trading data for each period can be obtained.

It can be divided into the following four according to the context of the purchase date, the sale date, the time A, and the time B (see FIG. 23).
(1) (3 when combined with the figures in Fig. 23) When the purchase date ≥ A time point (purchase date is after point A) and the sale date is less than B time point (sale date is before B time point) In other words, AB For trading data that completed trading during the period, the trading data below the trading profit / loss is evaluated. FIG. 25 is the corresponding figure.
(2) (4 when combined with the figures in FIG. 23) When the purchase date is ≥ A (the purchase date is after the A point) and the sale date is ≥ the B point (the sale date is after the B point), that is, A. For trading data purchased after the time point and held at point B time, the trading data below the unrealized profit / loss is evaluated.
(3) (2 when combined with the figures in Fig. 23) When the purchase date is <A time point (purchase date is before time A) and the sale date is <B time point (sale date is before B time point), that is, A For trading data that was held during the period but completed during the AB period, the trading data below the trading profit / loss is evaluated.
(4) (1 when combined with the figures in FIG. 23) When the purchase date is less than the time A (the purchase date is before the time A) and the sale date is ≥ the time B (the date of sale is after the time B). For trading data purchased before the time point and continuing to be held at the time point B, the trading data below the unrealized profit / loss is evaluated.

FIG. 24 of the unrealized profit / loss trading data is a table showing that the purchase price of 6.06 million yen is 8.84 million yen at the A time point evaluation value and 12.11 million yen at the B time point evaluation value (see also FIG. 100). .. FIG. 27 shows a method in which only the A time point evaluation amount and the B time point evaluation amount are displayed without indicating the purchase amount. Both displays are possible.

As described above, another feature of the trading data to be aggregated other than the evaluation change by the information processing system is to grasp it by dividing it into these four methods. The trading data for the AB period can be roughly divided into these four categories, and if you grasp this classification, you can understand how to grasp the results for each period and the correct answer. This four classification method is also one of the present inventions. However, when the stock price at time B is the current price, the stock price at time A can be revalued, but when the current stock price has passed time B, the stock price at time B needs to be revalued. Alternatively, the evaluation change at the time A is performed with reference to the trading data at the time B. In this way, trying to accurately capture the period profit and loss becomes quite complicated.

On the other hand, in the case of the third similar form of trading data subject to aggregation by period, the difference between the valuation amount at time A and the valuation amount at time B is obtained, which is the increase / decrease, and the increase / decrease in unrealized gain / loss is A. Assuming that the increase / decrease in trading profit / loss is B, since trading is complicated, accurate trading profit / loss and unrealized profit / loss during the period cannot be obtained. Period comparison of total profit / loss, which is the first level, trading profit / loss and unrealized profit / loss at time A, and trading profit / loss and unrealized profit / loss at time B are available. Does not come out. However, in this case, it is necessary to capture the stock price in chronological order, and there are various drawbacks compared to the full version. However, the calculation is a simple and easy-to-understand method, but the processing applied to the completed version from here is, after all, synonymous with the trading data to be aggregated (completed version). Whether or not it is a method of creating trading data subject to aggregation by period depends on the evaluation reassessment and the four classification methods.

(Effect of trading data subject to aggregation by period)
The step of creating the trading data subject to aggregation by period enables evaluation for each period, and makes it possible to more clearly evaluate the trading status and holding status for each period to be aggregated. In particular, by classifying into four types, the unrealized profit / loss formation fund and the trading profit / loss formation fund are evaluated separately, which has a great effect of clearly separating the holding status evaluation to be aggregated and the trading status evaluation.

As shown in FIG. 27, the purchase date, the purchase unit price, and the purchase price may be rewritten as the time point A, the time point A market price, and the time point A evaluation value. As shown in FIG. 24, another item may be added to the trading data to perform revaluation. The relationship between the market price at time B, which will be described later, and the current price is also the same. FIG. 24 includes a stock price recommended for buying (or a unit purchase price), a base price (or a market price at time A), and a market price at three time points of the latest closing price (or the market price at time B, the current price). FIG. 27 includes a stock price recommended for buying (or a unit purchase price) and a market price at two time points of the latest closing price (or the market price at time B and the current price).

By the above operation, each profit and loss is shown as a profit and loss for each period, and it exerts a remarkable effect not found in the old method. Needless to say, it is very useful to convey the situation where the trading data subject to aggregation by period changes from moment to moment. It can be said that it is indispensable trading data for creating current affairs. For example, the stock ranking 10 lost this week, what was the first place in the trading profit ranking yesterday, what made the most profit today, etc. can be easily created by creating the trading data to be aggregated by this period. , Is one of the purposes, and for that purpose, it shows a method of creating trading data to be aggregated by period.

All of these correct results are displayed from the trading data subject to aggregation by period, but if it is a pseudo version, even if the total profit / loss level is obtained, it will be displayed incorrectly because there are defects after the trading data of the trading profit / loss level. .. This is because, although it is actually trading data at the trading profit / loss level, it may be included in the trading data at the unrealized profit / loss level, and vice versa.

However, even if there are defects, there are some that are partially correct, so this method is also a form of trading data subject to aggregation by period. Summarizing these, there are four forms of trading data subject to aggregation by period, one is a method of capturing only trading profit and loss by period (first similar system), and the second is the total profit and loss by the relevant information processing system. The method of grasping by valuation change (second similar system), the third is the method of first dividing into trading profit and loss and unrealized profit and loss, and then the method of dividing into period profit and loss (third similar system), and the fourth is the complete version. ..

(Handling of deposit / withdrawal data of trading data subject to aggregation by period)
The handling of deposits and withdrawals during the AB period is also one of the complicated issues. At the time of A, it has changed from 1 million yen to 1.2 million yen at the time of B, and even if it increases by 200,000 yen, in the case where 100,000 yen is actually deposited and increased, this deposit is removed and the result is calculated. Must be. On the contrary, if 100,000 yen is withdrawn, the withdrawal is 100,000 yen with an increase of 300,000 yen. There are various methods for deposits and withdrawals during this period. The important thing is to separate the increase / decrease due to investment profit / loss during the period from the increase / decrease due to deposits and withdrawals. By separating this, it becomes possible to reliably calculate the increase / decrease due to the pure investment profit / loss.

(Regarding similar forms of trading data subject to aggregation by period)
(First similar form: Definition of creation and display of trading data subject to aggregation by period of trading profit / loss level)
This first-like aggregated trading data by period extracts only the trading data bought and sold during the period and compares the period.

(Problems of conventional technology)
It is surprisingly difficult to compare the period of investment results. The more data you have, the harder it is to understand. It is easy to understand if it is explained by a simple example of FIG. 23 above. It is this first similar form that captures the results of the AB period with only 3. If you sell the stocks you own, the stocks you buy and the stocks you have, or the stocks you have, they are all ignored, and only the buys and sells that you buy and sell during this period are calculated. It is not possible to grasp the actual situation by any means, and since it is evaluated only with the data of the AB period of the trading level trading data (only the trading data bought after the time A and sold before the time B), there are many omissions and reliability. It is not a number that can be done.

(First similar form: Action of creating and displaying trading data to be aggregated by period of trading profit / loss level)
Trading profit / loss level It can be created by extracting trading data, buying after time A, and extracting only trading data sold before time B. In the explanation of FIGS. 24 to 28, only the middle and lower stages of FIG. 26 are targeted. With this, the period profit and loss will be -240,000 yen. The actual situation is a plus of 3.54 million yen, so you can see how far the numbers will be.

(First similar form: Effect of creating and displaying trading data subject to aggregation by period of trading profit / loss level)
It is easy and useful to evaluate the skill of buying and selling without considering the holding situation. As an evaluation of short-term trading such as day trading, it is simple, simple, clear and easy to understand.

(Second similar form: Definition of creation and display of trading data subject to aggregation by period of trading profit / loss level)
This type of the second similar form is a period comparison that can be given when the trading data is stored in chronological order and is grasped as the numerical value of the entire valuation amount. It is a type that can change the valuation amount and compare the period.

(Problems of conventional technology)
In the first similar form, the achievements of those who own it are missing, so it is not possible to make an accurate judgment. This is because if you happen to have it at the time of B, you will be out of the list. In comparison, the second similar form has no omissions. It covers from 1 to 4.

(Second similar form: Action of creating and displaying trading data to be aggregated by period of total profit / loss level)
The second-similar form of trading data to be aggregated by period is to compare the periods using the total profit / loss level trading data. In other words, if there is a total of the market value, cash balance, and trading profit / loss of the stocks currently held, the current valuation amount is calculated. If both the valuation amount at the time of A and the valuation amount at the time of B are stored in the database, they can be obtained immediately. Common portfolios, cash balances, and valuations can be seen at each securities company when data is stored in this way, the valuation transition is the main target for period comparison.

(Second similar form: Effect of creating and displaying trading data subject to aggregation by period of total profit / loss level)
The whole picture is very easy to understand. Since you can see at a glance how much your valuation is and how it has changed, anyone can understand it and it is easy to compare the period. From this time last year, it is obvious that the valuation has increased or decreased in one year.

(Definition of trading data subject to aggregation by period (third similar form))
There is a method of first dividing the trading data into trading profit / loss level trading data, which is the second level trading, and unrealized profit / loss level trading data, and dividing them by period at the time B. Total profit / loss at time B-The total profit / loss at time A is the total profit / loss for the period, and the total figures for the unrealized profit / loss at time B and the trading profit / loss at time B are correct. come. However, the total numbers are correct, and this is defined as the trading data (third similar form) to be aggregated by period.

When the trading data at the time A is stored as time-series data, it can be obtained by adjusting the trading data at the time A, the trading data at the time B, and the trading during the AB period. The information processing system can create the period-specific aggregated trading data of the third similar form by dividing the portion where the valuation amount increases or decreases between ABs as profit or loss. In this case, the unrealized profit / loss at time B can be grasped by adding 1 and 4 to the unrealized profit / loss, and the trading profit / loss 2 and 3 are added to the trading profit / loss. There is no defect in the total profit and loss. Since the period profit and loss can be grasped more correctly than the second similar form, this is defined as the trading data to be aggregated by period in the third similar form.

(Problems of conventional technology)
Although there are defects, the trading profit and loss and the unrealized profit and loss can be displayed separately from the trading data subject to aggregation by period of the total profit and loss level, and it becomes easier to understand than a simple period comparison of the valuation amount.

(Action of trading data (second level) subject to aggregation by period)
The trading data is first divided into the trading data of the trading profit / loss level of the second level trading data and the trading data of the unrealized profit / loss level (first step), and it is divided into the trading data at the time B and the trading data at the time A for a period. Find profit or loss (second step). The total figures including the trading profit / loss at time B, the unrealized profit / loss at time B (third step), and the total profit / loss are correct. Since it is possible to capture the transition of the valuation amount (fourth step), the investment result of the period is more accurate than the total profit / loss level (second similar form) and the period comparison of trading profit / loss (first similar form). It has the effect of being able to be grasped.

(Effect of trading data (second level) subject to aggregation by period)
The level will be higher than in the second similar form, where the period can be compared only by the total profit and loss and the total assets, and it will be possible to better grasp the profit and loss by period. It is expected that Mr. A will be able to understand the total profit and loss ratio for 2020, and that the investor ranking will also be able to issue the total profit and loss increase rate ranking for this month.

(Concrete example)
The biggest problem is the buying and selling of the stocks held at the time of A, which were sold during the period. This changes from the unrealized profit / loss level trading data at the time A to the trading profit / loss level data at the time B. In order to process the trading data at time B, these stocks must be changed to the stock price at time A, or accurate numbers will not come out. After all, you cannot proceed to the next process unless you go through the processing process of the trading data to be aggregated (accurate numbers do not come out).

Further, in the third similar form, in the example of FIG. 23, there is no problem because 1 is included profit / loss level trading data, but since the revaluation is not performed, even if there is a total number, this number does not match. 2 is a case where the unrealized gain / loss level trading data changes to the trading / profit / loss level trading data. There is a defect in. 3 and 4 can be accurately obtained based on the time B.

(Definition of trading data (complete version) subject to aggregation by period)
Of the four methods, the investment results for each period can be measured most accurately using the trading data to be aggregated.

(Problems of conventional technology)
When measuring investment results by period, the biggest problem is that the investment products that you own and the investment products that you buy and sell are mixed, and if you divide by period, you can understand how to understand this result. It is to disappear. Brand rankings are easy to create. This is because it is not necessary to take the step of possession or non-holding depending on the rate of increase or decrease or the rate of decrease. On the other hand, in the case of investment results, it is difficult to compare the periods. It is very complicated, especially when it comes to big data, it is difficult to swallow why the numbers do not match, which is the result of this investment result by period.

In addition, the biggest drawback of the third similar form is that the stocks held have changed significantly between the trading data at time A and the trading data at time B, and stocks that were not at time A came in or were at time A. There are many exchanges between the unrealized profit / loss level trading data and the trading profit / loss level trading data because the stock has been sold and disappeared. Therefore, it is not possible to accurately grasp the status of unrealized gains / losses and trading profits / losses unless it is grasped by a method that is captured by the trading data (complete version) subject to aggregation by period. In other words, there is still the problem that the evaluation of the holding status and the evaluation of the trading status cannot be performed correctly.

It is easier to change the valuation amount, and it is expected that the trading data to be aggregated by period can be obtained, and the effect of knowing how the increased amount has increased can be expected. The former is sufficient for mere calculation of changes in valuation amount and rate of increase / decrease, but considering the later process, creation of trading data to be aggregated by period that accurately separates the results of owned stocks and the results of trading stocks. Is very effective. Here, if the trading data subject to aggregation by period is redefined, the trading data subject to aggregation by period (complete version) sandwiches the process of revaluation.

(Action of trading data (complete version) subject to aggregation by period)
The steps are surprisingly easy. In the trading data at time B, the unrealized gain / loss level trading data is divided into the portion purchased before the time A and the portion purchased after the time A, and the trading data at the trading profit / loss level is also the trading data held at the time A. By dividing into trading data that is not held at time A and revaluing the trading data held at time A at the market price at time A, it is possible to create trading data (complete version) to be aggregated by period. It's like a puzzle that you can't solve unless you solve it unexpectedly. It's surprisingly easy to solve, but it's difficult to understand only by trial and error.

To supplement FIG. 23 a little, 1 case is the part where the holding continues to increase or decrease, 2 case is the increase or decrease realized by selling the owned product, and 3 is the pure buying and selling during the period. , The part that increased or decreased, 4 is the part that I did not own until now, but purchased a new one and increased or decreased. By dividing this, the effect of clarifying the reason for the increase or decrease during the period can be expected. More than just increasing or decreasing the valuation, more things become clear. For example, it is necessary to divide the valuation between those who have increased their assets just by holding them during this period and those who have increased their assets by buying and selling hard during the period. When I try, I don't understand this. If the recently purchased item is in good condition, 4 will increase, if the item you have previously owned is in good condition, 1 will increase, if the trading is in good condition, 3 will increase, and the stocks sold during the period will contribute. Since 2 cases increase, more detailed evaluation becomes possible. In particular, a high effect is recognized in later processes (advice, diagnosis, etc.). Capturing the results of the period by revaluation and these four classifications is the two characteristics of the trading data (complete version) to be aggregated by period.

(Effect of trading data (complete version) subject to aggregation by period)
This effect is enormous. This is because the results of each period of investment results can be correctly understood. Who had the highest investment results in February 2020, whether there were many people who won the stock in November 2020, or whether there were many people who won the virtual currency, etc. This is because it cannot be derived without the concept of revaluation of data and trading data (complete version) subject to aggregation by period.

(Specific example of trading data (complete version) subject to aggregation by period)
It can be used for all of the investment results and the period, such as being able to generate the data necessary for articles such as Softbank stocks, exploring the investment results in 2020 in detail, and so on. FIG. 100 is a diagram summarizing FIGS. 24 and 26 showing a specific example of FIG. 23.

FIG. 28 is a diagram showing a table example of trading data to be aggregated by investor according to the present embodiment.

(Definition of trading data to be aggregated by investment target period)
It is a form of trading data subject to aggregation by period, and relates to trading data subject to aggregation by investment target. Investors' profits and losses by period are usually performed by methods such as valuation changes, but for investment target trading data by period, the investment profits and losses of issue A by period are calculated by the information processing system. Point to. It is this investment target trading data that can be aggregated by period that can generate content that solves the problem of how the investor's achievements in 2020 of the A brand were.

(Conventional issue)
At the individual level, the results of buying and selling investment targets can be obtained immediately, but it is unknown what happened to the investors as a whole.

(Action of trading data subject to aggregation by investment target period)
However, if the information processing system creates the trading data to be aggregated for each period of the investment target and the information processing system generates the data, there is a special effect that the generation can be easily performed. In particular, it will be possible to generate content such as "Investment results of company S stock, how about 2020?" By period, and it will be possible to generate a large number of article content. For that purpose, it is first necessary to create the trading data to be aggregated by period, and then this creation step and then the step to extract the investment target as the axis are required. There is a step of calculating various evaluation indexes by the information processing system in the calculation step of the profit / loss level evaluation index by the information processing system, and many evaluation indexes are calculated. Of course, it may be created first from the profit and loss level trading data (in no particular order).

(Effect of trading data subject to aggregation by investment target period)
For the first time, you will be able to understand the actual state of investment results by investment target period. Various contents are created by the combination of the period, the investment target, and the investment profit / loss. The information processing system can consistently generate contents such as rankings and comparisons.

(Specific example of trading data subject to aggregation by investment target)
(Specific example 1)
By combining the investment target, period, profit / loss, and stock price chart (setting each condition), the actual purchase price at the time of purchase such as each investor and the average of investors and the stock price at the time of sale are plotted on the stock price chart. It is possible to create a chart that can be used.

(Specific example 2)
By combining the investment target with the period, profit and loss, and technical indicators, the most effective technical index values for the period and the issue can be calculated by the information processing system, and various technical index values can be compared.

(Specific example 3)
By combining the investment target with the period, profit and loss, and corporate performance trends, it is possible to report how the performance news of the stock has changed the investment behavior during the period.

(Specific example 4)
By combining the investment target with the period, profit and loss, and stock news, it becomes possible to understand how the difference in investment behavior was made by the stock news during the period, and which news had the most impact on the investor.

(Specific example 5)
Combining investment targets with periods, profits and losses, and events will give you an idea of how dividend decisions and split decisions have changed investment behavior, much like stock news.

(Significance of trading data by component of trading data subject to aggregation by period)
When you want to see the investment results in 2020, there are many needs to look at the contents in more detail and analyze them. In particular, it is convenient for those who are engaged in short-term trading to know at a glance which stocks, how much profits they have made, and which stocks have had the largest losses. Such trading data subject to aggregation by period is further classified into components, and the trading data that has been re-aggregated (or does not have to be aggregated) is defined as trading data by component of the trading data subject to aggregation by period.

(Problems of conventional technology)
Even with simple trading data subject to aggregation by period, numbers for each period are available, so there is more to be understood. However, it is possible to combine the trading data by component, such as how it was by stock, which stock produced results in 2020, and if it was a stock or virtual currency, which one achieved results. It's convenient.

(Action of trading data by component of trading data subject to aggregation by period)
When the information processing system creates trading data by component of trading data subject to aggregation by period, the data is aggregated by brand, which is very easy to understand. First, the information processing system creates the trading data to be aggregated by period, then the trading data is classified by brand and aggregated by issue, so that the component trading data of the trading data to be aggregated by period can be created. ..

(Effect of trading data by component of trading data subject to aggregation by period)
Not only the combination of period and stock classification, but also, for example, if you use product classification instead of stock classification, you can easily compare the investment results of stocks and FX, and if you look at corporate performance, you can compare profit-increasing stocks and profit-decreasing stocks. However, using the classification as a technical index value, it becomes possible to easily compare the trading data purchased with an RSI of 20% or less and the trading data purchased with an RSI of 80% or more. It is the information processing system that can extract various data sets in all directions, but the components included in the trading data (for example, brand, brand) are based on the trading data by component of the trading data subject to aggregation by period. Since it is possible to classify and compare based on all kinds of data such as stock prices associated with dates, technical indicators, corporate performance associated with stocks, etc., various contents can be generated.

(Meaning of trading data by component of trading data subject to aggregation by period (by technical index))
I mentioned that you can do various things by creating trading data by component of trading data to be aggregated by period. What can you do about one technical index? It can be used to verify how the results of the technical indicators in 2020 were, and it can also measure the usefulness of the technical indicators. We can verify how the RSI can be used to be more successful in the 2020 period.

(By component of trading data subject to aggregation by period (by technical index) Action of trading data)
First, the information processing system creates the trading data to be aggregated for each period in 2020. Next, the technical index, which is one of the components, is classified by the index called RSI. If you want to know whether the purchase timing was successful, classify by RSI at the time of purchase. There are various classification methods, but for example, it may be classified into less than 20%, 20% or more and less than 50%, 50% or more and less than 80%, and 80% or more. When classified and aggregated in this way, the information processing system creates the 2020 trading data aggregated in each RSI range. If you can do it so far, follow the same steps after the 4th step as usual. The winning percentage and the trading profit / loss ratio are also shown, so you can see at a glance which range the purchase was successful.

(Effects of trading data by component of trading data subject to aggregation by period (by technical index))
The information processing system is an information generation system that can meet a wide variety of needs. It can be analyzed deeply and can generate article content for a wide range of media. The trading data by component (technical index) of the trading data to be aggregated by period is useful for people who want to look deeply at stocks from various angles such as day traders. It is a form of trading data subject to aggregation by period.

(Specific examples of trading data by component of trading data subject to aggregation by period (by technical index))
(Other specific examples by component of trading data subject to aggregation by period)
(Specific example 1)
One form of trading data by component of trading data subject to aggregation by period is by technical index. For example, what happens if it is a component of corporate performance? If the technical index of the above-mentioned action process is classified as RSI, the investment results of the stocks revised upward in 2020 and the investment results revised downward can be easily compared. .. Such an effect can be realized only by the trading data by component of the trading data to be aggregated by period by the information processing system. It can be said that such information is also useful as content such as stock newspapers.

(Specific example 2)
One form of trading data by component of trading data to be aggregated by period is by technical index, but it is also effective when, for example, it is desired to easily compare a successful person and an average index. Successful people assume that "investor: = 2020 results will have an overall profit / loss ratio of 30% or more". In this case, first, as usual, the information processing system creates the trading data to be aggregated for each period in 2020. "Investment type = successful person" (The definition of successful person is to make an investment type by investment type in advance with a group of investors who will perform with a total profit / loss ratio of 30% or more in 2020). If you classify the trading data to be aggregated by period in 2020 into the classification of successful people and average as the component of investment type, the aggregated value will come out, and as usual, if you follow the 4th step and after, the evaluation index of both will be easy. Can be compared to.

There are endless examples of trading data by component of trading data subject to aggregation by period. The reason why such data comes out is the consistency of the information processing system. In the second to fourth steps, extraction conditions, classification conditions, and aggregation rules are determined, and trading data sets are determined. This is because an evaluation index is calculated from this trading data set by the information processing system, and evaluation, comparative ranking, diagnosis, and advice are performed using the evaluation index, all of which make sense. The trading data subject to aggregation by period is only the first step.

Everything that follows is organically linked and contributes to the generation of various content.

(Significance of creating profit / loss level trading data of trading data subject to aggregation by period)
After the creation of the trading data to be aggregated by period, there are components, and there is a step to create the trading data of profit / loss level (there are steps that can be omitted, and the order is random). I will touch on. It is the creation of this profit / loss level trading data that defines whether the profit / loss in 2020 is viewed at the total profit / loss level, the trading profit / loss level, the unrealized profit / loss level, or at what level.

When measuring the investment results of the entire stock in 2020, if it is measured at the total profit / loss level, the transition of the valuation amount will be appropriate. If you can see the investment results of Mr. A by period, this level is the majority. Changes in valuation amount can be said to be a typical example. The next level is the second level trading profit / loss level trading data and unrealized profit / loss level trading data. In order to see this, as mentioned in the section on trading data subject to aggregation by period, a step of revaluation is required. That is why even if the profit for each period is known at the total profit / loss level, it becomes unclear at the trading profit / loss level and the unrealized profit / loss level. Therefore, the significance of the trading data subject to aggregation by period will be demonstrated in the fields after the second level of profit and loss. In other words, it is difficult to generate all the evaluation indexes generated from the creation of trading data subject to period aggregation and trading data whose profit / loss level is second level or higher (second level, third level, etc.) unless proper processes are taken. Become. Unrealized gain / loss level by period In the example of trading data, in order to correctly evaluate the results of 2020 at the unrealized gain / loss level, it is necessary to evaluate the stocks held at the beginning of 2020 and the stocks purchased during the period in 2020. It is necessary to manage the results separately, and up to this point, the evaluation indicators such as the win rate and the unrealized loss rate, which are the next steps, are correctly calculated by the information processing system, and the ranking and comparison are properly aligned. It can be measured with sex.

(Issues of existing technology)
In order to properly look at investment profits and losses by period, it seems that we know but often do not know how to correctly recognize unrealized gains and losses and trading profits and losses. What are the investment outcomes of 2020? You'll find that it's not that simple, considering what period of profit or loss you'll get if you buy something before 2020 and sell it up in 2020. There are various cases, and in order to achieve results in 2020, if you do not handle the database after understanding this, you will get different results. Unrealized gains / losses are the unrealized gains / losses at the present time, and will fluctuate daily during 2020, and buying and selling are complicatedly involved. It is the concept of trading data subject to aggregation by period and profit / loss level trading data that solves this technical problem.

(Profit and loss level of trading data subject to aggregation by period Effect of creating trading data)
The trading data subject to aggregation by period needs to be reassessed as described in the process of creation by the information processing system. This evaluation change is the first step. After this revaluation is completed, the second step is to separate the unrealized profit / loss level trading data and the trading profit / loss level trading data. Of course, the order can be reversed. In the case of each period, it may be easier to understand by dividing the unrealized profit / loss level trading data and the trading profit / loss level trading data and revaluing them. In the case of this step, the unrealized profit / loss level trading data revalues the stocks held at the time A to the stock price at the time A, and the trading profit / loss level trading data changes the stocks held at the time A to the stock price at the time A. A step to change the evaluation with is required.

(Effect of creating profit / loss level trading data of trading data subject to aggregation by period)
By this step, the unrealized gain / loss in the AB period will correctly display the trend of the unrealized gain / loss in the AB period, and the trading profit / loss in the AB period will also be correctly displayed.

It's surprisingly a blind spot that even securities firms don't take these steps, and the more data they have, the more complex they are, and the less visible they are, the more accurate the period. I can't make a profit or loss. Not to mention the third level and beyond.

(Specific example of creating profit / loss level trading data of trading data subject to aggregation by period)
For example, the stocks held in early 2020 continued to rise throughout 2020, doubling and selling. What kind of contribution will this be made by period? Those who think that the results in 2020 will be doubled cannot correctly evaluate the period profit and loss. The results will vary greatly depending on when you have owned it, and the rise in 2020 and the past will be mixed. This will produce inconsistent numbers. The correct answer is that the value obtained by subtracting the stock price at the beginning of 2020 and the stock price sold in 2020 is the result of 2020, and if it is doubled, the past results are also mixed. Ordinary portfolios have valuation transitions, but valuation transitions are used when valuing portfolios by period because otherwise they cannot be displayed correctly. Steps are required for unrealized gains and losses and trading gains and losses.

(Significance of calculation of trading data subject to aggregation by period and evaluation index by the relevant information processing system)
This is also related to the above. At the total profit and loss level, evaluation indicators are available. The transition of the valuation amount, the valuation amount at the time of A, etc. refer to this. But what about the winning percentage? There are various movements during the AB period between the trading data at the trading profit / loss level and the trading data at the unrealized profit / loss level. Looking at the previous example, it is the unrealized profit / loss level trading data at the time of A, but it becomes the trading profit / loss level trading data between AB, and the profit / loss is fixed. This is the moment when the unrealized gain or loss changes to the trading gain or loss. It is the complexity of transaction data that contains a lot of such data in various forms, such as how to calculate the winning percentage correctly. Therefore, if the trading data subject to aggregation by period is not calculated correctly, the profit and loss level trading data can only be known at the first level, and the evaluation index can only be obtained at the first level.

(Action of calculation of trading data and evaluation index to be aggregated by period)
All are linked. If any of the creation of trading data to be aggregated, the creation of trading data below the second profit / loss level, and the calculation by the information processing system of various evaluation indexes is missing, a maze will be entered. In the information processing system, each step is consistently operated in cooperation. That is why automation is easy to proceed and various data can be generated. Even in this step alone, the trading profit / loss level trading data is created by the information processing system in cooperation with the trading data to be aggregated by period, and the trading profit / loss level evaluation index (win rate, etc.) is linked from the trading profit / loss level trading data. It will be generated.

(Effect of calculation of trading data and evaluation index to be aggregated by period)
Even the very simple question of what is the investment result of Mr. A in 2020 cannot be answered that the system is consistent and not linked. Furthermore, if the trading data for each component is included in this, it will become more complicated. Because it is consistently linked, it is possible to answer even complicated requests and generate various contents.

(Specific example of calculation of trading data and evaluation index to be aggregated by period)
For example, when issuing a winning profit margin ranking by issue in January 2020, the difficulty level will increase as soon as the limitation of January 2020 is added, and the issue that is actually owned may be included or the issue that is owned first may be included. It is very difficult to put out accurately unless you properly define what to do if you sell the stock inside. Consistent ranking display is possible only by following the steps of creating trading data to be aggregated by period, creating component trading data, and creating profit / loss level trading data (in this case, the third level). It has a special effect of becoming.

(Definition of trading data and evaluation steps to be aggregated by period)
What does it mean to evaluate the results of Mr. A's stock investment in January 2020? It is to evaluate the trading situation correctly and to evaluate the holding situation. Again, the difficulty level will increase when the period of January 2020 is added. There are complicated factors in the situation of holding at the beginning of January, the trading situation during January, and the holding situation held at the end of January, so it is not so easy to evaluate.

(Problems of conventional technology)
The easiest way to evaluate how it was in January is to look at the changes in the valuation. If you know how much your assets have increased, you will feel like you have somehow understood. However, this does not lead to improvement. I don't see any improvement measures, why it didn't increase in January and how it will increase in February. This level is the total profit and loss level and is the first level of the profit and loss level.

(Aggregation target trading data by period and the action of the evaluation step)
If there is no mechanism to take a deeper look, it will not be improved. In the information processing system, the information processing system creates trading data based on the trading data subject to aggregation by period, trading data by component, and profit / loss level trading data from the second level onward, and the evaluation index is calculated from the trading data. Then, by taking further selection steps, KPIs suitable for the current user are derived, and improvement proposals and evaluations are made with those KPIs, so consistent rules are used, and no matter who does it, the same objective numbers are used. Can be evaluated based on.

(Trading data subject to aggregation by period and evaluation step effect)
Based on the KPI that the user had in January 2020, the evaluation of the holding status is decided and the evaluation of the trading status is decided, so an unprecedented effect can be expected.

(Comparison step with trading data subject to aggregation by period)
How can I compare Mr. A's investment results in 2020 and 2019? If you create the trading data to be aggregated by Mr. A and create the trading data for each component by dividing the year into 2020 and 2019, you will be ready. At this time, unless the computer is instructed to define the years 2020 and 2019 in the trading data, it cannot be properly separated. Here, the same procedure as for the trading data subject to aggregation by period is required. Since the points A at the beginning of 2019, B at the end of 2019, and the end of 2020 are required, accurate guidance cannot be achieved unless consistent rules are followed. The rules for FY2019 and the rules for FY2020 are determined according to the rules of the trading data subject to aggregation by period, and through that process, the evaluation index is calculated by the various information processing systems, the KPI is also determined, and appropriate comparisons can be made. .. The comparison between 2019 and 2020 of brand A and the comparison of day trading type are all the same. With the information generation system, various contents can be generated by instructing the computer consistently with all of these requests. Refer to the above evaluation step and comparison step for issues, actions, effects, etc.

(Trading data and ranking steps to be aggregated by period)
The ranking steps are similar. The procedure up to the selection of KPI is the same as the comparison step, and ranking is based on KPI. For example, Mr. A's investment results are ranked by year, and it is possible to grasp which year was the best or the worst in the annual ranking from 2010. This is also content that can be generated for the first time after properly following the steps for each period, each component, and the KPI, but the generated content (annual investment ranking, etc.) itself also took this process. Defined as content. Please refer to the above evaluation step and ranking step for issues, actions, effects, etc.

(Trading data and diagnostic steps to be aggregated by period)
The diagnostic steps are similar. It will be possible to see the past history while dividing the results by period, based on the trading data subject to aggregation by period. Refer to the above-mentioned evaluation step and diagnostic step for issues, actions, effects, etc.

(Specific examples of trading data by component of trading data subject to aggregation by period (by technical index))
Aggregation by period Refers to the classification and aggregation of trading data by technical index, which is a component. It can be used to verify what was the high technical index for Mr. A's investment results in 2020.

(Definition of trading data subject to aggregation by investor)
For example, if the aggregation target is an investor, the information generation unit 3021 may include an individual investor group, an institutional investor group, an individual investor A, an institutional investor B, an investor type group centered on short-term trading, or a medium- to long-term. Investor type of holdings Aggregate trading data by investor type such as group investors. In addition, the evaluation index of the trading data to be aggregated for all investors is calculated and evaluated by the information processing system, and the group classified by those evaluation indexes is defined as the trading data to be aggregated by investor in the trading data evaluation classification. In short, after evaluating the trading data of investors, reclassifying it and grouping it is defined as the trading data to be aggregated by investor in the trading data evaluation classification.

(Relationship with the old method of trading data subject to aggregation by investor)
The trading data according to the first embodiment does not include the item of investor. However, in reality, there are investors B and C, and there are various extraction methods such as investor groups and investment types.

(Issues of trading data subject to aggregation by investor)
By dividing the trading data for each investor, it is possible to create trading data to be aggregated by investor. From the trading data by investor, profitability, win rate, unrealized profit, etc. by investor, investment group, investment type, etc. can be known.

(Action of trading data subject to aggregation by investor)
The trading data obtained by extracting the trading data by the investor is defined as the trading data to be aggregated by investor. Specifically, the information generation unit 3021 adds the investor identification information to the item of the trading data according to the first embodiment, and sets the investor or investment group, institutional investor or individual investor in yet another table. Match the items by adding an item that identifies investment type A or B. As a result, it is possible to create trading data subject to investor aggregation from various perspectives. This example is an example and includes all the methods used to classify and aggregate investors by some criteria.

28 and 29 are diagrams showing an example of another table of the aggregated trading data by investor and the aggregated trading data by investment target according to the present embodiment. As shown in FIG. 29, in the information generation unit 3021, for example, Mr. Tanaka is an individual investor and a dividend yield-oriented type (investment type 1), and Mr. Nakamura is an individual investor and a short-term sheathing type (investment type 2). Create a table that displays the characteristics of each investor and link them in the database.

As a result, it is possible to derive the aggregated results of the short-term arbitrage type investor group (aggregated by investment type 2), and the short-term arbitrage type group (aggregated by investment type 2) and the dividend yield-oriented type (aggregated by investment type 1). It has the effect of being able to clarify the difference between buying and selling and the difference in profit and loss.

This kind of information is also useful as an article for the media. You can easily create articles such as short-term arbitrage type vs. dividend yield-oriented type, which one won in 2020, shareholder benefit type and dividend yield-oriented type, and what is the difference in results. This is a special effect of linking the investor table and the trading data to be aggregated by investor in a separate table. It is possible to have such an item in the item of trading data instead of a separate table, but it is difficult to manage and it is not recommended. However, the type included in such items is also a type of trading data subject to aggregation by investor. All methods such as incorporating investor attributes into the database, re-aggregating, extracting, and classifying are included in the trading data to be aggregated by investor.

The investment type classification mentioned in the investment type diagnosis may be applied here.

(Effect of trading data subject to aggregation by investor)
It has the effect of making it possible to understand whether each investor, each investor group, and each investment type are really profitable, losing, what the profit margin is, and what is going on this year. It can be said that this is also information suitable for article distribution. The information that can be generated by an information processing system is diverse and can be used in various ways. In addition, by dividing investors into investor groups and aggregating them, it is possible to know the results of each group's life and type, the difference in buying and selling between individual investors and institutional investors, and the difference in holdings. There is a remarkable effect that the old method does not have.

(Specific examples of trading data subject to aggregation by investor)
It is also useful to create this investor-specific aggregate trading data for creating article data for 2019 and 2020 for all investors and article data for stock investors and cryptocurrency investors. These are also generated data suitable for article distribution.

This kind of classification is possible simply by increasing items such as age and gender, such as investors who emphasize shareholder benefits, investors who emphasize dividends, foreign investors, female investors, and investors aged 65 and over. However, this is the trading data subject to aggregation by investor. There are many possible ways to approach investors, such as those who live in Tokyo, those who live in rural areas, salaried workers, OL investors, and investors who have reached retirement age. The results are divided according to the classification of, and the articles with titles such as salaryman investors vs. investors who have reached retirement age, what is the difference in results, etc. attract the attention of many people. It is the information processing system that can be verified, and the creation of the trading data to be aggregated is the first step.

(Definition of trading data subject to aggregation by investor in trading data evaluation classification)
As mentioned earlier, after evaluating the trading data of investors, reclassifying it and grouping it is defined as the trading data to be aggregated by investor in the trading data evaluation classification.

(Problems of conventional technology)
There is a concept of copy trading that imitates a good investor. Although the concept is a little similar, copy trading refers to the position that other individual traders publish and automatically copy and hold the FX position held in real time. It is commonplace in FX. This is also a service that was conceived from the concept that if there are good people, it will be helpful if they imitate it, but the trading data to be aggregated by investor in the trading data evaluation classification is for people who have made various trades. It is possible to easily classify and generate various investor groups based on the indicators that come out from the actual trading data.

(Action of trading data subject to aggregation by investor in trading data evaluation classification)
As a creation procedure, the information processing system first creates aggregated trading data for all investors, the profit / loss level is created up to the fourth level if possible, and various evaluation indexes are calculated by the information processing system. Now you're ready to go. Therefore, let's assume that the standard is to create a group with the top 10 total profit and loss ratios. With evaluation index = total profit / loss ratio, the trading data is sorted in order of total profit / loss ratio, and the top ten are defined as the top 10 members of the total profit / loss ratio. Of course, it will be updated from time to time, so if you link it to the date and put it in the top 10 member table of the total profit and loss ratio, it will be accumulated. Extracting only the trading data of the member is defined as the trading data to be aggregated by investor in the trading data evaluation classification of the member. The member is defined as the top 10 member of the total profit / loss ratio in the trading data evaluation classification.

(Effect of trading data subject to aggregation by investor in trading data evaluation classification)
Various groups can be created by the above processing. This effect is enormous. This is because if you select a target member depending on what kind of investor you want to be and what kind of buying and selling you want, you can refer to the buying and selling that the member is doing. In particular, when determining the holding status of a stock held in an evaluation step or the like, it will be possible to derive from the past history what the probability of being a target member is high. It can be used to judge the trading situation, and even by comparing it with the evaluation value of the group in the comparison step, it will give various notices.

(Specific examples of trading data subject to aggregation by investor in the trading data evaluation classification)
In addition to the above, in the diagnostic step, it is possible to tell what is the difference between the tendency that can be seen from various trading data of the group and the tendency of Mr. A. Various service developments that meet the needs of users can be considered.

(Definition of trading data subject to aggregation by time-series investors)
It is a kind of trading data to be aggregated by investor, and the link between the trading data of the database related diagram (see Fig. 91), the stock price data, and the stock price news is the purchase date (or purchase date and time) of the trading data, the stock code, and the stock news. By having a relationship (for example, see FIG. 91) with a date (or date and time) and a stock code in the table, it is possible to import stock news at the time of purchase into a database of trading data. By doing so, you can see how the stock that you purchased on the day of a certain stock news developed after that, and when you sold it, you made a profit and what was the profit margin. This is defined as trading data subject to aggregation by time-series investors. The feature is the buying and selling data including the stock price data, technical index value, stock news, etc. that have a relationship (for example, see Fig. 91) with the purchase data and sale data of the trading data and the date (or date and time) and the stock code. There is a kind. The trading data to be aggregated by time-series investment target, which will be described later, is centered on the investment target, but this is centered on the investor, and is intended to strengthen the ability to give advice to investors.

(Problems of the conventional method)
Stock price searches, chart displays, and stock news searches are usually everywhere. Various effects can be expected by linking this information with trading data.

(Action of trading data subject to aggregation by time-series investors)
In the database-related diagram (see FIG. 91), the trading data in which the trading data is associated with data such as stock news, stock prices, and technical index values exerts various effects in the subsequent processes. In other words, this association is maintained even in the profit / loss level trading data, so not only can the transition of the technical index value from the time of purchase, the transition of the brand news, etc. be tracked in chronological order, but also the information processing system of the evaluation index can be used. It also means that the relationship with the calculation can be tracked in chronological order. If the stock price rises, the value of the evaluation index rises, and the value indicating the overheating of the technical index appears, the current technical index value, the trading profit and loss when selling now, the change of other evaluation index values, etc. Will also be able to tell.

(Effect of trading data subject to aggregation by time-series investors)
By linking trading data with stock prices, charts, stock news, etc. that can be generally managed in chronological order, it is possible to exert unprecedented effects as mentioned above, generate advice, generate diagnoses, and to users. The quality of information provided by the company will increase to an unprecedented level, and the effect of making it easier to update the ranking display on a daily basis can be expected.

(Specific examples of trading data subject to aggregation by time-series investors)
As mentioned earlier, the special effect of being able to associate trading data of a stock with stock news, technical indicators, and trends in corporate performance can be expected. Furthermore, if you combine the unrealized P & L level trading data with the stock information, you can get news of the stocks you own, technical indicators of the stocks you own, signs at the time of sale, repurchase signs, early receipt of split announcements, daily updates of rankings, etc. Various effects can be expected, such as updating comparison results, displaying diagnosis results in time series, and displaying diagnosis history. It is a service that can contribute to improving services for investors from various angles. Evaluation step (can be used to judge the holding status), ranking step (stock ranking according to the holding period), comparison step (comparative increase / decrease rate with the average value after purchase, etc.), diagnostic step (holding stock related to the holding period after purchase) It contributes to everything such as diagnosis), advice steps (suggestions on what to do now based on these results).

(Definition of trading data to be aggregated by investor at the time of trading)
The time of purchase or sale is an important time when trading data changes. Information at that important time is extremely valuable. Nevertheless, the information at this time is usually buried over time, and I continue to hold it unconsciously, and before I know it, I have an unrealized loss or leave it without noticing the change in the situation. It is usual to get rid of it. Trading data to be aggregated by investment target at the time of trading is created to manage information at the time of trading, which is such an important time.

(Problems of the conventional method)
Usually, stock news, technical indicators, daily market news, etc. are numerous, and it is not easy to manage the information necessary for oneself. It contains a lot of information that you don't need to buy or sell, and you can't tell the difference between what you need and what you don't.

(Action of trading data subject to aggregation by investor at the time of trading)
Trading data to be aggregated by investor at the time of buying and selling plays a role of linking purchase data and sale data with stock news, technical index values, performance information, and the like.

The information on the investment target at the time of purchase or sale is information related to the buying and selling decision, and is much more important than the day when the buying and selling was not done. For that, the following effects can be expected by linking the date and brand code of the purchase table with the information related to the investment target such as the technical index value and news information of the day.

(Effect of trading data subject to aggregation by investor at the time of trading)
By linking the performance from the time of purchase with the judgment at the time of purchase, it is useful for verifying whether the judgment at the time of purchase was correct later, the judgment at the time of sale, and always making the wrong judgment in the same place. Because of this, it becomes possible to judge that the results have not been achieved. This trading data to be aggregated by investor at the time of trading can be expected to have a remarkable effect of giving investors an unprecedented awareness.

(Specific examples of trading data to be aggregated by investor at the time of trading)
In addition to the above examples, by linking the performance at that time, the performance forecast of the society at that time, rating information, etc., it is useful for various verifications, rules are established, and patterns are successfully found. It makes it easier to find the cause of failure and the cause of success.

(Definition of trading data subject to aggregation by event management investor)
The above-mentioned trading data to be aggregated by time-series investment target connects time-series data and trading data, but the trading data to be aggregated by event management investment target is not time-series and is irregular on a specific or unspecified day. Information related to event-type investment targets that occur in Japan is linked to trading data.

(Problems of the conventional method)
There is a wide variety of information related to investment, but the information that is necessary for oneself is buried and cannot be distinguished. Usually, the most important information for an investor is information about the stock purchased. Of course, many investors care about this information, but in the current situation where there is a lot of news, everyone has once experienced that it is overlooked or only noticed over time without knowing important events. .. Event management Aggregated trading data by investment target solves such problems.

(Action of trading data subject to aggregation by event management investor)
For example, if you purchase A-shares on August 1st and continue to hold the stock, it will become a supervised stock in the unrealized profit / loss level trading data. The event information of the stock associated with the stock code (there are various events such as rights information such as dividends and stock splits and shareholder benefit information) may be notified before the event occurs, or later. Although it may be notified, it is possible to create a mechanism to be provided to the user by some method such as e-mail or display, because of this event management investment target aggregation target trading data. Until now, important information that had to be managed by oneself is automated.

(Effect of trading data subject to aggregation by event management investor)
Not only can you notify the occurrence of an event, but you can also know the changes after the event has occurred, and it is possible to provide information that contributes to the decision to buy or sell. For example, it is possible to tell that the shareholder coupon has been granted rights today, or that an unexpected event has occurred in the investment target held and everyone is making a judgment. These may be possible by a method that does not use this event management investment target aggregation target trading data, but content generated by such a method, including such a method, is subject to event management investment target aggregation. Defined as trading data content.

(Specific examples of trading data subject to aggregation by event management investor)
There are many events to manage, such as dividend increases, split announcements, newspaper news, and a sharp increase in the number of cases handled on Twitter for the investment target. Since you only have to manage the investment targets you own, there are few checks and it can be said that the content is highly effective.

It is a service that can contribute to improving services for investors from various angles. Evaluation step (one that can be used to judge the holding status, and can be issued at the time of the event where the upward revision occurs, such as the winning percentage of the issue for which the upward revision was announced after purchase) and the ranking step (profit increase announcement) You can easily get the ranking of the rate of increase / decrease for one month after the event that the event occurred), comparison step (you can compare how much the result differs depending on the information correction range in the upward revision event), diagnostic step (after the event occurs) Diagnosis based on the results is also possible), advice steps (suggestions on what to do now based on these results), etc. will contribute to everything.

(Definition of trading data subject to aggregation by investor)
Indispensable for achieving the results of stock investment targets is to properly update the trends in corporate performance and capture changes. By linking trading data with the corporate performance of the stocks held, it is possible to quickly grasp changes in the business performance of the stocks held.

(Issues of trading data subject to aggregation by investor)
In the conventional method, not only the stocks held but also information related to various business performances are announced every day. However, it also contains a lot of information that is not necessary for me. The most necessary thing is the performance trend regarding the stocks held.

(Effects of trading data subject to aggregation by investor)
It is not difficult in itself to grasp the performance trends of the stocks held. EDINET is updated daily, and there are many ways to grasp its performance trends in real time. However, if it is linked to trading data and connected to the information processing system, it will have a special effect. For example, by linking the unrealized profit / loss level trading data with the holdings, the performance data and the holdings are related. Numbers such as past performance trends and future company forecasts are also relevant. As time goes by from the time of purchase, it is difficult to manage many trends related to business performance, such as announcement of revision of business performance, announcement of business performance, and revision of forecast figures.

(Effects of trading data subject to aggregation by investment target)
However, by using this system and the trading data subject to aggregation by investor, for example, the earnings revision of stock A (purchase price 800 yen) purchased on August 1 was revised upward on August 26 (stock price 810). (Yen), the forecast revision was announced on September 5, and the results were announced at the same time, and good results were produced (stock price 950 yen). Then, in the case where the profit was finally confirmed at 1300 yen after the final sale on October 30, it will be displayed on the chart at the time of each announcement, the unrealized profit will be reported to be increasing, and the actual value of the business performance will be displayed. It will be possible to immediately check how much the difference between the two has increased. Also, for later verification, you can check the stock price trend after the announcement of the upward revision at a glance, how much the impact on profits will differ depending on the size of the upward revision, and how long you sold from the announcement. It will be possible to use it as a material for investment decisions such as whether it is better to keep it or whether it is better to keep holding it. These will make it possible to provide information that has never been seen before.

This is also a service that can contribute to improving services for investors from various angles. Evaluation step (It can be used to evaluate the holding status, and it is possible to display a list of the performance trends of the stocks held and the time series data after that, as well as to immediately capture and display how much the results differ depending on the profit increase range and correction range. For example, if there is an announcement that deviates from the 30% forecast, it will be possible to immediately inform you of what kind of price movement was on average in 10 days when such an announcement was made.) Ranking step (For example, it is possible to compare the trading profit margin ranking of the upwardly revised stock), comparison step (for example, comparing the actual trading winning rate of the profit-increasing stock and the active stock), diagnostic step (after the earnings announcement) (Diagnosis based on the results of), advice steps (suggestions on what to do now based on these results), etc. will contribute to everything.

(Significance of calculation of trading data and evaluation indexes subject to aggregation by investor by the relevant information processing system)
After creating the trading data to be aggregated by investor, there are components, and there is a step to create profit / loss level trading data (there are optional steps, in no particular order). I would like to touch on the relationship between. It is the creation of profit and loss level trading data that defines whether the profit and loss of investor A is viewed at the total profit / loss level, the trading profit / loss level, the unrealized profit / loss level, and the investor. When measuring the investment results of A as a whole, if it is measured at the total profit / loss level, the transition of the valuation amount will be appropriate. Changes in valuation amount can be said to be a typical example. The next level is the second level trading profit / loss level trading data and unrealized profit / loss level trading data. The trading data of investor A is created by separating the trading data and the non-trading data, and the evaluation index is calculated. It is possible to gradually calculate effective and easy-to-use evaluation indexes such as winning rate and winning profit rate.

(Problems of conventional technology)
In the first embodiment, “the trading data of the investment product is acquired, the basic numerical value (basic data) is acquired from the acquired trading data, and the evaluation index regarding the trading profit / loss and the unrealized profit / loss is calculated from the acquired basic numerical value, and the calculated evaluation is performed. The evaluation index related to the total profit and loss is acquired from the index, and the information indicating the acquired evaluation index is generated. " The problem with existing technology is that it is difficult to meet various demands because it is based on a calculation formula. For example, what is the winning percentage of Mr. A in 2020? Which brand contributed the most? There was a problem that it was difficult to meet various demands. Further, since the first embodiment is an evaluation index calculated from transaction data (trading data in a narrow sense), there is a problem that the evaluation index that can be acquired is not widespread and the evaluation index can be calculated only when it is decided.

(Effect of calculation of trading data and evaluation index to be aggregated by investor)
On the other hand, in the fourth embodiment, the aim is to link the databases, and by setting various conditions from the second step to the fourth step, it is possible to change the shape of the trading data to be worked on according to the purpose. In the above example, by setting the period to 2020 or using the components as stocks, the trading data can be easily transformed into a shape that suits the purpose, and for the trading data that has changed according to this purpose. Since the process of calculating the evaluation index is taken, the evaluation index suitable for the purpose can be easily derived by the information system. Furthermore, for the second issue, as a result of being able to capture not only transaction data but also market data, technical data, and all other information related to investment profits and losses, the range of evaluation indicators that can be calculated by the information processing system is wide. It spreads and it became possible to see the object from various angles. This is also the result of database linkage, and this consistent collaboration system overcomes the above-mentioned problems.

(Effect of calculation of trading data and evaluation index to be aggregated by investor)
As described above, the fourth embodiment can handle various targets (for example, comparison between silver generation investors and salaried workers) in various forms according to the purpose of investors, and further. , The target can take in not only transaction data but also information necessary for improving the profit and loss of the target (for example, linking corporate performance information and technical information with trading data), and the information processing The calculation of evaluation indicators by the system is a technological innovation that has the special effect of expanding and deepening the range.

(Definition of trading data to be aggregated by investment target)
The investment targets to be aggregated include stocks such as company S stocks, investment trusts, stocks such as ETF bull funds, stocks such as FX yen dollars, and virtual currency stocks. In addition, stocks can be grouped and aggregated into stock group, high-quality stock group, high-dividend stock group, etc., as well as stocks with upward revision of business performance, Chinese-related stocks, index investment trust group, robot fund group, etc. It becomes one of the aggregation targets. Furthermore, products, product groups, etc. are also included in the total. The information generation unit 3021 divides trading data for each aggregation target such as virtual currency, FX, stocks, etc. (extracts according to extraction conditions), (aggregates according to classification criteria), or aggregates each (aggregates according to aggregation conditions). ), Create aggregated trading data by investment target. A plurality of aggregate target trading data may be combined into one and extracted according to the extraction conditions. Furthermore, price information, which is one of the attributes of investment targets, technical index values, and the like are also included in the components of the trading data to be aggregated by investment target.

(Relationship with the conventional technology of trading data subject to aggregation by investment target)
The trading data according to the first embodiment contains an item indicating an investment target called a brand code. The first embodiment also specifies that the code is for specifying the stock of the stock to be bought and sold. However, in the first embodiment, it is not extracted, classified or aggregated for each investment target. In addition, securities companies generally have information such as portfolio information that conveys the status of their stocks. It also contains stock information and stock price information. This is the information of Mr. A in the trading data subject to aggregation by investor. The trading data to be aggregated by investment target is trading data extracted and re-aggregated from the information of the A brand, and is completely different. The former is the chart of A brand owned by Mr. A, the latter is the chart of A brand, but you can see where the average buys, sells on average, and in what price range many people buy. Is a service that can only be performed with the latter trading data that is subject to aggregation by investment target.

This is because the former is based on the trading data captured under the extraction condition of Investor A, and the stocks there are one of the components, and only the trading information of Mr. A is not linked. On the other hand, if the trading data to be aggregated by investment target with the A issue as the extraction condition is used, the trading data of Mr. A is also included, and the trading data of other Mr. B and Mr. C are also included, so how to use it. Is completely different.

(Problems of conventional technology)
By giving conditions for trading data for investment targets, it is possible to create trading data to be aggregated for each investment target. A lot of information on investment targets is provided as stock information. There are various information such as financial information, charts, and brand news. However, only fragmentary information is available on how investors buy and sell the stock and how they are making a profit. There is a problem that the whole picture is completely unknown and it is wrapped in a veil. Although the stock of company S is rising, there is no information on the situation of the people who own it, how much profit the people who bought and sold will make in 2020, and so on. However, according to the information processing system, profitability, win rate, unrealized profit, etc. by brand and product can be known by starting from the trading data to be aggregated by investment target. Information will be further expanded by linking with brand news and charts. Doing this with investment-specific aggregated trading data has a special effect. This is a form of aggregated trading data by investment target, and is a form in which purchase data and sale data are linked to investment targets. This is of great importance and has a great effect, so I will separate it later.

(Action of trading data subject to aggregation by investment target)
The information generation unit 3021 uses the investment target table (etc.) to extract and classify the above-mentioned aggregated trading data for each investment target (extraction process under extraction conditions) or classify (later components). (Different from classification) or aggregated by aggregation rules (calculation of total or average value, etc.) to create aggregated trading data by investment target, and trading profit / loss level evaluation index or unrealized gain / loss from aggregated trading data by investment target Calculates the level evaluation index, etc., and generates information related to the evaluation of the trading status or holding status of each investment target.

Aggregation target trading data by investment target is obtained by extracting (or classifying or aggregating) trading data for each investment target. In the trading data according to the first embodiment, the stock code is taken as an example, but it becomes more effective if this is used as the investment target code. Further, as shown in FIG. 29, by specifying the investment target code as a stock, virtual currency, or ETF product classification, specific stock code, or grouping in another investment target table. Various investment targets can be evaluated from various perspectives.

By creating trading data to be aggregated by investment target, it is possible to create articles such as stocks and virtual currencies, which one is actually profitable. Indeed, it can be used as an article material for the media. In order to be able to create such articles, it is necessary to create this aggregated trading data by investment target. Normal trading data is managed for each investor (trading data subject to aggregation by investor), and has not been re-aggregated for investment targets across the board. If you recount the data on the axis of investment target, you can expect a big effect that you can see various new discoveries. In addition, as mentioned above, when the investment targets are managed separately in a separate table, and when the item of trading data is created, it is the trading data to be aggregated by investment target. If you divide the investment target into some criteria and use the trading data to create an article, it is a necessary process in most cases to create the trading data to be aggregated by investment target, but even if you do not include this process, The content created by dividing the investment target using the trading data is defined as the trading data content to be aggregated by investment target.

(Effect of trading data subject to aggregation by investment target)
You will be able to understand whether the investment target is really profitable or losing, what the profit margin is, and what is the current year. For example, you can know the commonality of the trading situation of stocks classified as trader stocks, you can know the average unrealized profit / loss ratio, you can know the tendency of individual investors to buy and sell excellent stocks and virtual currencies, etc. There is a special effect that the people who buy and sell in the stock of company S can understand how to sell and how many people own it by creating it with the information processing system.

Normally, in order to create such content, it is not possible to create it without creating this aggregated trading data by investment target, but all investment targets are all content creation methods that recapture the trading data centered on the investment target. Defined as trading data content subject to separate aggregation. One example is the results of trading data aggregation by brand.

(Specific examples of trading data subject to aggregation by investment target)
(Specific example 1)
For example, an upward revision of the business performance of a stock (a stock whose actual value exceeds the expected value of the company's business performance is called an upwardly revised stock) or a downward revision of the business performance (when the actual value is lower than the expected value of the company's business performance). It is possible to easily calculate the issue of the subsequent trading profit rate and winning rate of the stock purchased after the announcement of the downwardly revised business performance by the information processing system using the trading data subject to aggregation by investment target. ..

Prepare a data table of issues, the date and time of upward revision of business performance, and the upward revision rate (calculated by the information processing system based on the actual value of operating profit / expected value of operating profit, etc.). By associating this table with trading data by issue (issue code) and date (purchase date or sale date), the issue can be given the date and time of upward revision of business performance (downward revision date and time in the case of downward revision) and the upward revision rate (upward revision rate). Downward revision rate) is linked.

Since the date and time of upward revision of business performance, purchase date, and upward revision rate are included in this trading data item in the trading data subject to aggregation by investment target, the number of elapsed days is one day (data purchased in one day after upward revision). If you create trading profit / loss trading data from trading data by investment target created under extraction conditions with an upward revision rate of 20% or more, and set the evaluation index to the winning rate and trading profit / loss ratio, you purchased stocks with an upward revision rate of 20% or more on the first day. The winning rate and the trading profit / loss rate of the case are calculated by the information processing system.

In this way, the aggregated trading data by investment target is called the aggregated trading data by investment target, such as extracting investment targets (in this case, upwardly revised stocks) under some conditions.

(Specific example 2)
For example, by extracting and aggregating only the 10th-ranked stocks with a high upward revision rate, it is possible to create trading data for each investment target of the stocks with a high upward revision rate.

The trading profit / loss level of the trading data to be aggregated for the investment target. When data is created and the trading profit rate and winning rate of the purchase data are aggregated, the winning rate, trading profit rate, and unrealized profit rate when the 10th upwardly revised stock is purchased on the first day after the upward revision can be displayed. All of these are calculated on the database, which is the effect of creating aggregated trading data by investment target.

By creating aggregated trading data by investment target, it is possible to link it with various investment target data in this way, and the market data, performance data, technical index data, etc. of the investment target, as well as the actual purchase data and sale data can be obtained. It has the special effect of being easily linked, making it easier to verify and create rules with a high probability of success.

(Specific example 3)
In the case of linking with the above-mentioned upward revision table, at least the purchase date, the purchase stock price, the purchase quantity, the date and time of the upward revision of the business performance, and the upward revision rate are linked to the information of the purchase data of the issue.

If the information processing system calculates the purchase date for each purchase data and the number of days elapsed for the date and time when the business performance has been improved and makes it one of the database items, the component trading data aggregated for each number of days elapsed since the upward revision is created. can. By doing so, it is possible to compare the trading data in the case of one day from the upward revision with the trading data purchased after the lapse of 10 to 20 days, and to know how the winning rate and the trading profit rate are different. These are also calculated by the information processing system on the database. When the trading profit / loss trading data is created and the trading profit / loss ratio ranking is generated using the trading profit / loss ratio as an evaluation index, the purchase data is displayed in a list in the order of the number of days elapsed when the trading profit ratio is high.

In this way, the more complicated processes are included after the aggregated trading data by investment target, the more difficult it is to understand that the process is sandwiched first, but how to utilize the trading data with the investment target as the starting point. The essential process itself is the trading data to be aggregated by investment target.

(Specific example 4)
For example, trading data by investment target of stocks (investment target = created by stock extraction conditions) and trading data by investment target of virtual currency (investment target = created by virtual currency extraction conditions) are traded by trading profit / loss level trading data. It is possible to compare by rate and win rate.

(Specific example 5)
Trading data by investment target of stocks (investment target = created based on stock extraction conditions), component trading data by brand (trading data by classifying trading data by investment target of stocks by brand) (It is possible to have it in the previous process) (Trading data created by extracting trading data by classifying trading data by investment target of stocks by stock only with trading data that has been counter-traded) If the rate is used as an evaluation index, the trading profit / loss ratio for each issue is calculated by the information processing system.

This year, company S stock was the best, company T stock was 50th, and so on. It can be said that such generated data is also article data for the mass media.

(Specific example 6)
You can also use the trading data to be aggregated by investment target for article data such as what is the most profitable stock in 2019 and 2020, and also for creating article data that this is the stock that is currently losing. It is useful to create this trading data to be aggregated by investor.

It is very difficult to create these articles without taking the steps of creating aggregated trading data by investment target, but it cannot be denied that they are all created. The source that creates such content is defined as the trading data to be aggregated by investment target.

In addition, it can be said that the ability to create various articles not only for individuals but also for the mass media and the mass media is one of the characteristics of the information on the trading data to be aggregated by investment target linked to the data of the investment target.

Normal trading data is aggregated for each investor, and it is a major feature of this aggregated trading data by investment target that a completely different perspective can be seen when the investment target is the axis. For example, how much trading profit is on average in buying and selling shares of Company S, how much unrealized profit is currently held, what is the average purchase price currently held, etc. have not appeared in the world until now. Information is produced. One of the processes for creating these contents is the aggregated trading data for each investment target.

As mentioned earlier, the special effect of being able to associate trading data of a stock with stock news, technical indicators, and trends in corporate performance can be expected. It is often linked to investor trading data, but if you focus on the investment target, you can see it from a completely different perspective. In addition, it is possible to know the average purchase price range of stocks from the trading data to be aggregated by investment target, and it is expected that the price range with many purchasers can be known. Such information is useful information for investors, but it is information that has never been released to the world. The more trading data is accumulated, the more possibilities and expansions there are, and the step of creating the trading data to be aggregated by investment target.

(Definition of trading data subject to aggregation by time-series investment target)
This time-series version is a form of trading data to be aggregated by investment target.

(Problems of the conventional method)
Ordinary chart information is formed by stock prices and time series, and what is displayed on the investor's screen is stock news and technical indicators. On the other hand, in the case of the trading data to be aggregated by investment target, it is possible to understand how all the investors are buying and selling the A stock with the A stock as the axis. On average, stock A is bought at a place with a high technical index and sold at a place with a low technical index, and a considerable trading loss is recorded. How I would do the opposite, the holders are currently having a lot of unrealized losses in stock A, and as they approach the average purchase price, the number of items for sale is increasing. Since the number of holders has not decreased yet, it is possible to make a decision such as selling it, which is an excellent effect of this time-series investment target aggregate trading data.

It is completely different from the conventional way of thinking, and investors will be able to obtain information that they could not know even if they wanted to know it.

(Effect of trading data subject to aggregation by time-series investment target)
You can always see the stock prices and charts of the investment target on the securities company website. However, there is no information such as who bought the A brand, where it was sold, and whether it is profitable or lossy on average. This can be easily done by creating the aggregated trading data by investment target. By displaying the investment target on a time-series chart or the like and displaying the actual movement of the investor on the chart in chronological order, it is possible to create the aggregated trading data for each time-series investment target.

(Effect of trading data subject to aggregation by time-series investment target)
I told you that if you re-aggregate from the perspective of investment targets, you will get a special effect, but by combining time-series data such as charts, you can expect even greater effects as mentioned above.

(Definition of trading data to be aggregated by investment target in another table)
Among the trading data to be aggregated by investment target, various data of investment targets can be imported by linking the information of investment targets managed in another table with investment targets (stock code, etc.). Such trading data is defined as trading data to be aggregated by investment target in another table. In the item of the above action, there is also "Extract the above-mentioned aggregated trading data for each investment target using the investment target table etc.", but since it is an important matter, this is referred to as the aggregated trading data by investment target in another table. Redefine. However, it naturally includes linking each investment target to the purchase or sale of the investment target. In the above, "As shown in Fig. 29, specify the investment target code as a stock, virtual currency, or ETF product classification, specific stock code, or grouping in another investment target table. Therefore, various investment targets can be evaluated from various perspectives. "This is also a form of aggregated trading data by investment target in a separate table. To explain in a little more detail, it is as follows.

There is a table that can be linked to the trading data to be aggregated by investment target. The trading data to be aggregated by investment target is defined as the trading data to be aggregated by investment target. There are cases where both the purchase date and the purchase date are related, and the meanings of the two can be different, but these are collectively defined as the aggregated trading data by investment target in a separate table. Normally, unless you associate technical indicators with purchase data, you will not be able to create content that results from the connection between the two, but such content is content created through this separate table investment target aggregated trading data, and vice versa. The method of creating content that arises from the connection between these two is defined as separate table investment target aggregation target trading data.

(Issues of trading data to be aggregated by investment target in another table)
Normally, conventional transaction data managed by a securities company or the like is managed separately from information on investment targets. By managing this information in a separate table and linking it with a brand code or the like, the information can be linked to trading data and various problems can be solved. By linking with purchase data, sale data, and trading data, various contents are created, and various advice and investment problem solving become possible.

(Effect of trading data to be aggregated by investment target in another table)
In another table, there are cases of relationship with brand information and cases of relationship with brand information and date (purchase date). Explaining the latter case, the investment target is decided at the time of purchase, and the investment target is sold at the time of sale. However, the information on the investment target at both points is taken in from another table, so that the investment at the time of purchase is made. By incorporating the target information and the investment target information at the time of sale into the database, a special effect can be expected in which the effect on trading profits and losses becomes clear. It is one of the above-mentioned information on the upwardly revised stocks, and it is also one of the forms of trading data to be aggregated for investment in another table. It will be possible to link various information on the investment target at the time of sale. As mentioned in the section on trading data to be aggregated by investment target, it is shown separately because it becomes even more important in the case of investment targets. The table relationship format further strengthens the various effects of creating trading data to be aggregated by investment target. Of course, other than the trading data to be aggregated by investment target, it can be defined as the trading data to be aggregated in another table, and can be used in the same way with other trading data to be aggregated. For example, by investment type is also a form of trading data to be aggregated by investor, but the table relationship format of trading data to be aggregated by investment target greatly expands the possibilities.

(Effect of trading data subject to aggregation by investment target in another table)
The item is added separately because it can make the creation of aggregated trading data by investment target even more attractive. In the trading data to be aggregated by investment target, the investment target and other data are mainly linked, and even this can be expected to have a large effect, but in this separate table method, not only the brand but also the purchase data and sale data are linked. The width can be further expanded by including attachment. It is the trading data to be aggregated by investment target that can manage trading by issue, and in addition, it is this trading data to be aggregated by investment target that can be linked with the purchase information at the time of purchasing the issue. .. Because, in order to associate with the information at the time of purchase, two items, date and brand, must be associated. It is more complicated than the issue-only association. Since it is difficult or impossible unless it is set in a separate table, it is defined as trading data to be aggregated by investment target in a separate table. The trading data of the investment target linked with the purchase data is defined as the trading data to be aggregated by the investment target in another table.

It also reports methods by investment type and using an investment target table, but it is specially defined because it has a wide range of applications and is more effective. As mentioned by investment type, the special effect is that investors can analyze from different angles by incorporating the information managed in another table into the trading data, and the investment target is also the result of the stock market. You will be able to see the investment targets from various angles by displaying the results of excellent stocks separately, and re-aggregating and reclassifying the investment targets. It is expected that many news articles will be born, and there are many discoveries and discoveries that have never been seen before.

(Specific example of trading data to be aggregated by investment target in another table)
(Specific example 1)
In addition to the above cases, for example, by associating a set of a stock and a date, if a separate table that manages the news of the stock, the date and the stock of the day is imported, the news of the stock can be imported into the trading data. Looking at these based on the investment target is the separate table investment target trading data. As with business performance, there are various types of events (for example, business performance announcements, capital increases, split announcements, announcement events, etc.), so the effect of incorporating this information into trading data by investment target is immeasurable. It will be possible to easily verify whether or not the shares purchased on the day of the announcement of the split will be successful.

(Specific example 2)
By referring to the table of technical index values of stocks, the technical index values of the day can be easily captured, and the accuracy and verification of the judgment can be performed. It is very meaningful to capture this in the trading data to be aggregated by investment target (this is also important, deep, and difficult to understand, so it is displayed separately).

(Specific example 3)
Indicators such as dividend yield and PER (Price Earnings Ratio) can also be linked to the purchase date and brand, so they can be imported. It will be possible to easily determine which trading profit / loss is larger, such as high-dividend stocks or non-dividend stocks. This is possible because it is the trading data that is subject to aggregation by investment target. This kind of information has never been released to the world and is of high value.

(Specific example 4)
For example, it is possible to compare the winning percentages of a stock with a high stock price forecast score and a stock with a low stock price forecast score. This is also the trading data to be aggregated for each investment target in another table, and is the content that can be generated only by the information system.

(Specific example 5)
In 2020, we will be able to answer issues such as financial stocks and high-tech stocks, and how different the trading profit margins are. It can be said that this is also content that can be generated because it is the trading data that is subject to aggregation by investment target.

In this way, the trading data subject to aggregation of investment targets in a separate table can be expected to have a special effect of making the analysis of trading data wider and deeper, so it was explained separately.

(Specific example 6)
You can also use the trading data to be aggregated by investment target in another table for article data such as competition of stocks and what is the most profitable stock, and to create article data that there are only so many people who lost in corona related stocks. However, it is useful to create aggregated trading data for each investment target of this separate table relationship. All of these contents are trading data contents subject to aggregation by investment target, and are contents that can be generated only by the information processing system. Because it is a consistent information processing system, it becomes content that can be easily extracted.

(Definition of trading data to be aggregated by investment target at the time of trading)
Buying and selling are important decisions for investors. What are the other investors actually doing when purchasing the A brand, what happened to those who bought it a week ago, and who bought it a month ago? I want to know such things. Such information can be distributed in the trading data to be aggregated by investment target at the time of trading. This is because if we look at the behavior of each investor from the perspective of investment target, it will be a completely different perspective.

(Problems of the conventional method)
The decision to buy or sell a brand is a self-judgment, and it is inevitable. When I hear opinions on bulletin boards, I am concerned about someone's advice and other people's actions.

(Effect of trading data to be aggregated by investment target at the time of trading)
By plotting investor behavior on a chart, you can understand the current situation of buying and selling. With this alone, content from various perspectives can be considered. By aggregating the trading data into component trading data by investment type, it is possible to clarify the investment behavior of each investment type before and after the time of purchase.

(Effect of trading data to be aggregated by investment target at the time of trading)
For example, in the case of day trading, there is a considerable amount of buying and selling between 900 yen and 950 yen, few people have long-term holdings, but medium- to long-term holders are buying at such a low stock price and are already so profitable. It gives us various notices, such as the fact that it is out. Since the perspective of the aggregated trading data by investment target changes significantly, it is commonplace in the aggregated trading data by investor, and it can be changed to fresh information. It is one.

(Specific examples of trading data to be aggregated by investment target at the time of trading)
Investors in Chinese stocks can see their investment behavior from various angles, such as what they are doing and what they are doing in US stocks.

(Definition of trading data to be aggregated by event management investment target)
The above-mentioned time-series investment target aggregation target trading data connects time-series data and trading data with the investment target as the axis, but event management investment target aggregation target trading data is not time-series, but is specific or unspecified. Information related to event-type investment targets that occur irregularly on a specific day is linked to trading data.

(Problems of the conventional method)
Event management by investor is also important, but if you focus on the investment target, the time and content of the event will be displayed on the chart of issue A, and the purchasers will see how other investors behaved at that time. It is possible to display from the viewpoint of what happened.

(Action of trading data subject to aggregation by event management investment target)
Created based on trading data to be aggregated by investment target. By linking the time of the event to be invested with the content of the event, it is possible to understand how the behavior of investors has changed.

(Effect of trading data subject to aggregation by event management investment target)
You can see how it works before and after the right to shareholder benefits, what happened after the announcement of the stock split, what happened after the stock split, etc. You can expect a special effect of becoming.

(Specific examples of trading data subject to aggregation by event management investment target)
There are many events such as dividend increase, announcement of split, newspaper news, and rapid increase in the number of cases handled on Twitter of the investment target. It can be said that the effect of being able to see the behavior of other investors at the time of the event is extremely large.

(Definition of trading data subject to aggregation by investment target)
Indispensable for achieving the results of stock investment targets is to properly update the trends in corporate performance and capture changes. By linking trading data and corporate performance centered on the investment target, it is possible to quickly grasp how other investors behaved when the performance of a stock changed.

(Issues of trading data subject to aggregation by investment target)
With the traditional method, performance trends can be obtained, but how other people are actually moving is veiled. When the upward revision was made, so many people went to buy it within a few hours after the announcement, but those who bought it will be able to get information such as what happened after that.

(Effects of trading data subject to aggregation by investment target)
There is always information on performance trends in stocks. Even if the information is linked to the issue and is linked to trading data, it is necessary to link it with the investment target as the axis. Then, the investor's behavior will be linked, and the investor's behavior will be understood by the announcement of the business results.

(Effects of trading data subject to aggregation by investment target)
It is also possible to display whether those who purchased immediately after the upward revision was announced have an unrealized loss, whether they have an unrealized gain, and how many people have bought or sold.

(Definition of trading data to be aggregated by investment target product)
In addition to stocks, investment target products include virtual currencies, FX, investment trusts, ETFs, REITs, and the like. These investment target products are managed in their respective accounts, and it is very difficult to make a cross-sectional comparison. From the results of Mr. A's transactions, it is still unknown to all investors which investment products were good in 2020 and which investment products had the highest average value. What you can see is the chart, such as the rise in this investment product in 2020. It can be said that there is no information such as how the actual sale was, how many participants were, and how it was.

(Problems of the conventional method)
Securities companies should have such data, but it is one of the information that has not been used in the world until now. However, it is very significant from a social point of view that investors and non-investors can confirm the buying and selling of those who have actually bought and sold. Until now, the mass media could not take up such data because there was no such information processing system. The information processing system is a system capable of providing such information.

(Action of aggregated trading data by investment target product)
Then, what kind of procedure should actually be used to extract such information? The purchase data has a brand code. This brand code is information associated with the product. The stock code XXX is the stock code of company S, but the stock of company S is a category of investment products called stocks. On the other hand, the virtual currency is a ticker symbol, BTC is Bitcoin, and if it is an investment trust, it is a brand code or an investment trust association code. These are all tied to investment products, which is why
If the trading data of investment products such as stocks to be aggregated by investment target and the trading data of investment products such as virtual currency to be aggregated by investment target are aggregated, the information system can be easily compared. It is a form of trading data to be aggregated by investment target.

(Effect of aggregated trading data by investment target product)
There is no time to take a closer look at investment products. If you look at the big picture, you can broaden your horizons, such as investment trusts are good now, or stocks are good now, so let's try a little. Of course, it is also possible to compare with financial products such as government bonds. However, it can be said that variable products are more effective. Investment trusts are not just held, they are bought and sold. It can be said that it is very effective if the actual situation can be grasped. If anything, this kind of information is for the mass media, and young women have recently purchased investment trusts, but it is possible to generate articles from various perspectives, such as what the actual results are. Such content is content that can be generated only from the aggregated trading data by investment target product in the information processing system, but such content is defined as aggregated trading data content by investment target product, including other methods. ..

(Specific examples of trading data subject to aggregation by investment target product)
There are many ways to deal with investment products that have never appeared in the world, such as which one is more successful, virtual currency or stocks, what is the actual state of FX investment, and what are the current people who actually purchased investment trusts. The actual situation becomes clear.

(Definition of trading data to be aggregated by investment target group)
The investment target products are divided into various groups. Among the stocks, Chinese stocks, US stocks, and Japanese stocks can be classified by country, and investment trusts can be divided into various groups such as monthly distribution type and open type. Among Japanese stocks, there may be stocks called the maker stock group and excellent stock groups. These are all defined as aggregated trading data by investment target group.

(Problems of the conventional method)
The actual investment status of these groups is also a black box. It is information that is not available in the world, such as what is happening to those who bought stocks and what is happening to those who continue to hold excellent stocks. The impact of these coming out to the world is great.

(Action of aggregated trading data by investment target group)
It can be solved by creating an investment target table. By associating the brand code with the group, if these aggregated data are the information processing system, it can be calculated. For example, it can be easily done by extracting the aggregated trading data of all the collected investors by the investment target group = Chinese stocks and the investment target group: Japanese stocks. It is important that the stock code is associated with Japanese and Chinese stocks, which is usually on the market and available to everyone. After that, if you re-aggregate and generate various data with the information processing system, various interesting generated data will come out.

(Effect of aggregated trading data by investment target group)
For US equity investors, the index is rising, but the reality is that those who are doing it have no idea what they are feeling now. If we can understand the actual situation of such investment, various people will be able to be interested in investment products, and it may be possible to greatly contribute to the imbalance between investment and savings compared to other countries. .. Although it is useful enough for investors, it is possible to derive content suitable for mass media that can generate a lot of articles that are of interest to even those who have never done investment products from this aggregated trading data by investment target group. Such contents can be generated only from the aggregated trading data by investment target group in the information processing system, but such contents including other methods are defined as the aggregated trading data contents by investment target group.

(Specific examples of trading data to be aggregated by investment target group)
You can generate articles from various perspectives, such as what is the actual investment situation of the stocks, what is the unrealized gain ranking of the holders of excellent stocks, and what is the actual investor in the representative FANG of the US stock group.

(About the content name)
The content generated by the aggregated trading data by investment target is named as the aggregated trading data generation content by investment target. The content generated by the trading data subject to aggregation by period is named as the trading data content subject to aggregation by period. The trading data to be aggregated by investor is named as the trading data content to be aggregated by investor. Similarly, if content is added under each name of the trading data to be aggregated (as well as ranking names, etc.), it is defined as a name representing the generated content. The contents that give these specific examples are synonymous even if the generation method is different.

(Definition of trading data to be aggregated by investment target by purchase date)
It is a kind of trading data to be aggregated by investment target. If the extraction condition: purchase date = for example, September 1, 2020, and the stock code = 9984 (SoftBank stock), the trading of SoftBank stock purchased on September 1, 2020. Data is collected. This is defined as the trading data to be aggregated by investment target by purchase date.

(Problems of conventional technology)
At present, it is almost unknown what kind of actions the people who purchase SoftBank shares have taken. The current situation is that you can only get an estimate from the trading value, trading volume, margin trading balance, etc.

(Action of trading data subject to aggregation by investment target by purchase date)
By creating trading data with the information processing system under the above extraction conditions, creating total profit / loss level trading data, and calculating from the trading data with the information system, for example, December 1, 2020. If this execution is performed on the information system on a daily basis, the actions of those who purchased Softbank shares on September 1, 2020 will appear in the evaluation index so that they can be picked up. It becomes clear that some investors still hold and have unrealized gains, some investors have failed by buying and selling many times, and some have succeeded.

(Effect of trading data subject to aggregation by investment target by purchase date)
It is a technological innovation, and it is possible to tell the trends of other investors regarding the holding status in the holding status evaluation, compare it with good people, and display the ranking. This effect brings various effects. Articles from various perspectives can be generated as article material.
.. (Specific examples of trading data subject to aggregation by investment target by purchase date)
For example, three months after the corona shock, how did investors behave? The information processing system can generate the data required for articles such as day trading.

(Definition of trading data to be aggregated by investment target by purchase period)
It is a type of trading data to be aggregated by investment target, and if extraction conditions: purchase date> for example, September 1, 2020, and purchase date <for example, December 1, 2020, issue code = 9984 (SoftBank shares), The trading data of SoftBank shares purchased between September 1, 2020 and December 1, 2020 will be collected. This is defined as aggregated trading data by investment target by purchase period.

(Problems of conventional technology)
The range is wider than the above-mentioned purchase date, and by setting the purchase period to, for example, one month or one year, the subsequent investment behavior of the stocks purchased during that period becomes clear. The so-called aggregated trading data by period clarifies the profit and loss of the period, but by purchase period, what kind of action is taken after the purchase for the purpose of clarifying the investment behavior of the investors who purchased during the period. Can be grasped.

(Action of trading data subject to aggregation by investment target by purchase period)
Under the above extraction conditions, the trading data to be aggregated by investment target is created, then the profit and loss level trading data is created, and various evaluation indexes are calculated by the information processing system. Behavior becomes clear.

(Effect of trading data subject to aggregation by investment target by purchase period)
It is possible to check changes in the trading tendency of this stock every three months, and to grasp the investment target from an unprecedented perspective. It can be understood from various perspectives, such as the percentage of people who continue to hold the investment after 3 months, and the difference in investment results depending on the holding period.

(Specific examples of trading data subject to aggregation by investment target by purchase period)
For example, how did investor behavior change before and after the corona shock? The information processing system can generate the data required for articles such as.
(Definition of trading data by component of trading data to be aggregated by investment target)
The aggregated trading data by investment target is trading data that is extracted, classified, and aggregated based on the investment target, and the aggregated trading data by investment target has components constituting it. Including transaction data such as the stock and product name of the investment target, purchase date and purchase price, sale date and sale price, stock information such as company information and corporate performance, market data such as stock price and technical index value, dividend All data that affect the investment profit / loss of the investment target, such as rights data such as splits and splits, is defined as a component, and extraction, classification, and aggregation (one or more) are defined by those components. The re-executed trading data is defined as trading data by component of the trading data to be aggregated by investment target.

(Problems of conventional technology)
By extracting, classifying, and aggregating trading data for each investment target, it is possible to create trading data to be aggregated by investment target. By extracting the data, it is possible to create trading data invested in stocks on 9/10. Then, the result of the 9/10 stock will be clear at a glance, and it will be clear how many people have bought and sold and what kind of buying and selling has been done. This alone is information that has not appeared in the world.

(Action of trading data by component of trading data to be aggregated by investment target)
If we take this one step further and classify by issue, it will be possible to create information such as which issue is winning and which issue is successful. By extracting trading data under various conditions and then extracting, classifying, and aggregating the stocks and other constituent elements that are the constituent elements, the trading data by component of the aggregated trading data by investment target is the relevant. Created by an information processing system.

(Effect of trading data by component of trading data to be aggregated by investment target)
By creating the trading data by component of the trading data to be aggregated by investment target by the information processing system, various evaluation indexes can be calculated by the information processing system. In the previous example, the breakdown of the people who purchased the stock on 9/10 by brand is calculated by the information processing system, and the trading behavior, holding behavior, etc. are clarified. The metrics calculated from this dataset can be used for valuation, diagnosis, advice, comparisons and rankings. For example, if you review the subsequent trends of stocks purchased in September six months later, you will see reports of various trends. And articles can also be created with the information processing system, and it is also possible to save them in chronological order.

(Specific examples of trading data by component of trading data to be aggregated by investment target)
(Specific example 1)
The evaluation based on the trading data by component of the trading data to be aggregated by investment target is described in detail in FIGS. 103 to 106. This is also a form, and is an invention that enables investors to be given a large number of discoveries and knowledge by the information processing system.

(Specific example 2)
(Comparison of trading data by investment target and trading data by component)
To give an example of comparison using trading data by component of aggregated trading data by investment target, the average rate of increase of stocks purchased on 9/10 and the rate of increase of stocks purchased by Investor A on 9/10. For example, you can compare with. This is an example when comparing (investment target) by evaluation index (calculated under the relevant conditions) for each (component). Comparing stocks A by investor's total profit / loss ratio and stocks by stock's trading profit / loss ratio or winning percentage are specific examples.

(Specific example 3)
(Ranking based on trading data by component of trading data to be aggregated by investment target)
Examples of rankings based on trading data by component of trading data to be aggregated by investment target include the ranking of the rate of increase of stocks purchased on 9/10 and the ranking of the trading profit / loss rate of stocks purchased on 9/10. ~ (Investment target) ~ (Component) ranking of evaluation indicators (calculated under the relevant conditions), ranking A stocks by winning percentage by investor, including stocks by stock, by profit / loss ratio or winning profit margin Ranking is one concrete example.

(Specific example 4)
(Diagnosis based on trading data by component of trading data to be aggregated by investment target)
To give an example of diagnosis based on trading data by component of trading data to be aggregated by investment target, diagnosis is made by the increase rate ranking of stocks purchased on 9/10, or by the trading profit / loss ratio of stocks purchased on 9/10. Then there is something like that. ~ (Investment target) ~ (Components) Diagnosis based on the evaluation index (calculated under the relevant conditions), Diagnosis of stock A by the winning percentage by investor, Inclusion of stocks by stock, profit margin and winning profit margin Diagnosis with is one specific example.

(Specific example 5)
(Advice based on trading data by component of trading data to be aggregated by investment target)
To give an example of advice based on trading data by component of trading data to be aggregated by investment target, advice is given based on the ranking of the rate of increase of stocks purchased on 9/10, or advice based on the trading profit / loss ratio of stocks purchased on 9/10. Then there is something like that. Advice using the evaluation index (calculated under the relevant conditions) of ~ (investment target) ~ (component), showing the winning percentage of stock A by investor and giving advice to increase it, and by stock Showing the unrealized profit / loss ratio and the winning profit ratio, and giving advice on the stocks held is one specific example.

(Specific example 6)
(Display of evaluation index based on trading data by component of trading data to be aggregated by investment target)
To give an example of displaying the evaluation index based on the trading data by component of the trading data to be aggregated by investment target, the evaluation index of the trading profit / loss ratio of the stock purchased on 9/10 is displayed, or the stock purchased on 9/10. For example, it displays an evaluation index called the winning percentage of. -Displays the evaluation index (calculated under the relevant conditions) of- (investment target)-(components), shows the winning percentage of issue A by investor, and shows the unrealized rate of return and winning profit margin by issue. That is one concrete example.

(Definition of trading data by component with investors as components of trading data to be aggregated by investment target)
The trading data by component with the investor as the component of the trading data to be aggregated by investment target is extracted from the trading data to be aggregated by investment target, for example, the purchase of issue A on 9/10 in the above example. The trading data (including trading data to be aggregated) classified, aggregated, and extracted (including one or more) is classified by the component called investor, and the trading data to be aggregated by investment target is the component of the investor. It is defined as trading data by component.

(Problems of conventional technology)
How investors have bought and sold investment targets has been veiled. Investors who invest in stocks have no idea how much profit or loss they have or how much unrealized profit they have, and it is not news. It is possible to solve this problem by creating trading data by component with the investor of the trading data to be aggregated by investment target as a component.

(Action of trading data by component with investors as components of trading data to be aggregated by investment target)
By setting the extraction conditions as investment targets and extracting, classifying, and aggregating them by the investors who are the components, the trading data for each component is created with the investors of the trading data to be aggregated for each investment target as the components.

(Effect of trading data by component with investors as components of trading data to be aggregated by investment target)
When this trading data set is created by the information processing system, the behavior of investors for each investment target is clarified, how they are making profits, whether they have such a loss, unrealized gains and losses and trading. A special effect can be expected in which the actual state of profit and loss can be seen. It is possible for the information processing system to generate articles that have a great impact not only on investor behavior but also on those who are not investing.

(Significance of creating profit / loss level trading data of trading data subject to aggregation by investment target)
After creating the aggregated trading data by investment target, there are components, and there is a step to create profit / loss level trading data (there are optional steps and in no particular order). I would like to touch on the relationship between. It is the creation of profit / loss level trading data that defines whether the investment profit / loss of stock A is viewed at the total profit / loss level, the trading profit / loss level, the unrealized profit / loss level, or the investment target A stock. When measuring the overall investment results, if it is measured at the total profit / loss level, the transition of the valuation amount will be appropriate. Changes in valuation amount can be said to be a typical example. The next level is the second level trading profit / loss level trading data and unrealized profit / loss level trading data. The trading data of the investment target A issue is created by separating the trading data and the unreversed trading data, and the evaluation index is calculated based on the non-equal trading data. It is possible to gradually calculate effective and easy-to-use evaluation indexes such as winning rate and winning profit rate.

(Issues of existing technology)
In the first embodiment, “the trading data of the investment product is acquired, the basic numerical value (basic data) is acquired from the acquired trading data, and the evaluation index regarding the trading profit / loss and the unrealized profit / loss is calculated from the acquired basic numerical value, and the calculated evaluation is performed. The evaluation index related to the total profit and loss is acquired from the index, and the information indicating the acquired evaluation index is generated. " The issue of existing technology is assumed to be Investor A, not from the perspective of the investment target, or even such a view does not come up. This is because it is impossible to calculate it in the first embodiment, and it is possible only by linking with a database. Since the first embodiment is based on a calculation formula, it is difficult to meet various demands. For example, what is the winning percentage of the A brand in 2020? Or, who was the investor with the highest investment performance of stock A? There was no such idea, and the narrow view of evaluating the trading data of Investor A was a major issue. Further, since the first embodiment is an evaluation index calculated from transaction data (trading data in a narrow sense), there is a problem that the evaluation index that can be acquired is not widespread and the evaluation index can be calculated only when it is decided.

(Profit and loss level of trading data subject to aggregation by investment target Creation of trading data)
In the fourth embodiment, in order to overcome these problems, the most important thing was to divide the roles of each department by linking the database, gradually narrow down the target according to the purpose, and narrow down the target trading data set. Revolutionary information with improved technology for evaluating various targets from various angles by creating and calculating various evaluation indexes with the information processing system based on the trading data. It is a processing system. By linking the databases and setting various conditions in the second to fourth steps, it is possible to change the shape of the trading data to be worked on according to the purpose. In the above example, by targeting the investment target instead of the investor, or by setting the component to the year, the trading data can be easily transformed to suit the purpose and changed according to this purpose. Since the process of calculating the evaluation index is taken for the trading data, the evaluation index suitable for the purpose can be easily derived by the information system. Furthermore, for the second issue, as a result of being able to capture not only transaction data but also market data, technical data, and all other information related to investment profits and losses, the range of evaluation indicators that can be calculated by the information processing system is wide. It has expanded and it has become possible to see investment targets from various angles. This is also the result of database linkage, and this consistent collaboration system overcomes the above-mentioned problems.

(Profit and loss level of trading data subject to aggregation by investment target Effect of creating trading data)
As described above, the fourth embodiment can handle various targets (for example, comparison between a trader stock group and excellent stocks) in various forms according to the purpose of the target of investment, and further, the target. It has become possible to capture not only transaction data but also information necessary for improving the profit and loss of the investment target (for example, corporate performance information and technical information and trading data), and the information processing system concerned. The calculation of the evaluation index by is an epoch-making technological innovation that brings about a special effect that the width is widened and the depth is deepened.

(Specific example of trading data by component with investors as components of trading data to be aggregated by investment target)
(Specific example 1)
(Comparison of trading data by component, with investors as components of the trading data to be aggregated by investment target)
To give an example of comparison using the trading data by component with the investor as the component of the trading data to be aggregated by investment target, the buying and selling of Mr. Z's A brand and the buying and selling of the investor A's A brand are as follows. Comparisons can be made using evaluation indicators such as trading profit / loss ratios and unrealized profit / loss ratios. This is an example when comparing (investment target) by evaluation index (calculated under the relevant conditions) for each (investor). Comparing stocks A by investor's total profit / loss ratio and stocks by investor's trading profit / loss ratio or winning percentage are specific examples.

(Specific example 2)
(Ranking based on trading data by component with investors as components of trading data to be aggregated by investment target)
To give an example of ranking by investor of the trading data to be aggregated by investment target, the trading profit / loss ratio ranking by investor of A stock or the winning rate ranking by investor of A stock is given. And so on. ~ (Investment target) ~ (For each investor) Ranking of evaluation indicators (calculated under the relevant conditions), ranking A stocks by win rate by investor, including stocks by investor, profit margin and winning profit Ranking by rate is one concrete example.

(Specific example 3)
(Evaluation based on trading data by component with investors as components of trading data to be aggregated by investment target)
The evaluation based on the trading data by component with the investor as the component of the trading data to be aggregated by investment target is described in detail in FIG. 106. This is also a form, and is an invention that enables investors to be given a large number of discoveries and knowledge by the information processing system.

(Specific example 4)
(Display of evaluation index based on trading data by component with investors as components of trading data to be aggregated by investment target)
To give an example of the display of the evaluation index based on the investor of the trading data to be aggregated by investment target, the evaluation index of the trading profit / loss ratio of the A issue by the investor is displayed. For example, displaying an evaluation index called the winning rate for each investor of a stock. ~ (Investment target) ~ (By investor) Display of evaluation index (calculated under the relevant conditions), showing the winning percentage of issue A by investor, and showing the unrealized profit margin and winning profit margin by issue It is one concrete example to aggregate and show each.

(Specific example 5)
(Diagnosis based on trading data by component with investors as components of trading data to be aggregated by investment target)
To give an example of diagnosis using trading data by component with investors of trading data to be aggregated by investment target as components, it is possible to make a diagnosis using the investor ranking based on the trading profit / loss ratio of stock A, or investors of stock A. For example, it is diagnosed by another trading profit / loss ratio. ~ (Investment target) ~ (for each investor) Diagnosis using the evaluation index (calculated under the relevant conditions), diagnosis of stock A by the rate of return by investor, and unrealized gains and losses of stocks by investor Diagnosis using the rate or the rate of return is one concrete example.

(Specific example 6)
(Advice based on trading data by component with investors as components of trading data to be aggregated by investment target)
To give an example of advice based on trading data by component with investors as components of trading data to be aggregated by investment target, we give advice to raise Mr. A's ranking in the trading profit / loss ratio ranking of stocks purchased on 9/10. Or, you can give advice based on the trading profit / loss ratio of the stock purchased on 9/10. -Advice using the evaluation index (calculated under the relevant conditions) of- (Investment target)-(Component), showing the winning rate of A stock by investor and giving advice to increase it, and investing in stocks Showing the unrealized profit / loss ratio and winning profit ratio for each house and giving advice on stocks is one specific example.

(Specific example of trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
(Specific example 1)
(Comparison of trading data by component with the investment target as the component of the trading data to be aggregated by investment target)
To give an example of comparison using trading data by component with the investment target as the component of the trading data to be aggregated by investment target, the trading of A stock and the trading of B stock among stocks can be compared with the trading profit / loss ratio or unrealized profit / loss. Comparisons can be made using evaluation indicators such as rates. When comparing (investment target) by (investment target) with the evaluation index (calculated under the relevant conditions), compare stock A with stock B by total profit / loss ratio, or buy and sell stocks by stock. Comparing profit and loss ratios and winning percentages is one specific example.

(Specific example 2)
(Ranking based on trading data by component with the investment target as the component of the trading data to be aggregated by investment target)
Examples of rankings based on trading data by component, which is based on the investment target of the trading data to be aggregated by investment target, include the trading profit / loss ratio ranking by stock and the winning rate ranking by stock of the trader. Will be. ~ (Investment target) ~ (For each investment target) Ranking of evaluation indicators (calculated under the relevant conditions), ranking of stocks owned by individual investors by unrealized profit rate, and winning rate of day trader trading stocks by stock Ranking by is one concrete example.

(Specific example 3)
(Evaluation based on trading data by component with the investment target as the component of the trading data to be aggregated by investment target)
FIG. 103 details the evaluation of the trading data by component, which is the component of the trading data to be aggregated by investment target. This is also a form, and is an invention that enables investors to be given a large number of discoveries and knowledge by the information processing system.

(Specific example 4)
(Display of evaluation index by trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
To give an example of displaying the evaluation index based on the trading data by component with the investment target of the trading data to be aggregated by investment target as a component, the evaluation index of the winning profit rate by stock of the stock owned by the individual investor is displayed. For example, it displays an evaluation index called the average rate of return on trading for each stock of short-term trading investors. ~ (Investment target) ~ (By investment target) Display of evaluation index (calculated under the relevant conditions). Showing the winning percentage of virtual currency by issue, and showing the unrealized profit / loss ratio and winning profit margin of stocks by issue is one specific example.

(Specific example 5)
(Diagnosis based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
To give an example of diagnosis using trading data by component with the investment target of the trading data to be aggregated by investment target as a component, trading by investor of stock A, which is diagnosed using the stock ranking based on the trading profit / loss ratio of stocks. Diagnosis is based on the profit / loss ratio. ~ (Investment target) ~ (For each investment target) Diagnosis using the evaluation index (calculated under the relevant conditions), diagnosing stocks by the winning percentage of each stock, and unrealized profit / loss ratio of stocks by stock Diagnosis using the winning profit margin is one concrete example.

(Specific example 6)
(Advice based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
To give an example of advice based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component, the stocks held are lower in the trading profit / loss ratio ranking among the stocks, and a minus is recorded. Providing advice while displaying that there are many people in the information processing system. Proposing higher stocks with the information processing system because the winning rate of the stocks held is low among the stocks, and providing advice. And so on. With the information processing system, advice using the evaluation index (calculated under the relevant conditions) of ~ (investment target) ~ (by investment target), showing the winning rate of stocks by brand, and increasing the winning rate. Providing advice, showing the unrealized profit / loss ratio and winning profit margin for each stock, and providing advice on the stocks held by the information processing system are specific examples.

(Definition of trading data subject to aggregation by technical index)
The technical indicators to be aggregated are the shapes of legs such as RSI, stop legs, hoshino legs, stick legs, squirrel legs, candle legs, technical indicators using the moving average line (moving average), and the Ichimoku Kinko Hyo. Technical index, MACD (Moving Average Convergence Divergence), DMI (Directional Movement Index), RCI (Rank Correlation Index), RSI (Relative Strength Index), W% R (Williams% R), Bollinger Bands, Stochastic Oscillator, Psychological Line, Includes technical indicators using parabolic, Pentagon chart, CCI (Commodity Channel Index), moving average divergence rate, MFI (Money Flow Index), etc. In addition, technical indicators can be grouped and aggregated into psychological line indicators, oscillator-based technical indicators, trend-based technical indicator values, etc., and candlestick shapes, appearing legs, etc. can also be aggregated. Become one. Furthermore, chart indicators and the like are also one of the aggregation targets. The information generation unit 3021, for example, links numerical values such as RSI and stochastic to purchase data and sales data, creates RSI calculated by the information processing system based on RSI, and further creates RSI to be aggregated. You may create trading data by component by technical index by dividing by the range of and summing up each. In addition, as shown in the above-mentioned separate table investment target aggregation target trading data, the technical indicators managed in the separate table are based on trading data (purchase data or sale data is also possible) and date (or date and time), brand and date. By linking it, it becomes easier to manage. This is also an example of the trading data to be aggregated by technical index, and is the trading data to be aggregated for investment by technical index in another table.

As shown in the database-related diagram (see Fig. 91), the date (or date and time) of the trading data, the stock code, and the date of the technical indicator value (in this case, the purchase data) and the technical indicator can be linked. Or by having a relationship with the date and time), it becomes possible. A short-term, fast-moving technical indicator requires a date and time, but if there is little movement during the day, it depends on the date and the nature of the technical indicator. Through this database linkage, trading data and technical index data are linked by date and brand, and the technical index value on the purchase date can be imported into the database. It is possible to verify whether or not the purchase data with RSI of 20% or less was successful.

(Relationship of trading data subject to aggregation by technical index with conventional technology)
Technical indicators are frequently used by investors, but are not used in combination with trading data (especially trading data). It is possible by inputting the value of the technical index in the transaction data, calculating it by the information processing system (including automatic and manual input), or referring to it from another table that manages the technical index. The purchase data is usually composed of the purchased brand, the purchase date, the purchase market price, and the like, and at that time, the technical index value can be calculated by the information processing system. By including this technical index value in the data (either later or immediately), it is possible to create trading data to be aggregated by technical index.

(Issues of trading data subject to aggregation by technical index)
Technical indicators are used to make buying and selling decisions, but by linking them to buying and selling data and managing them in a database of buying and selling data, it becomes possible to verify later, and I believe that it is a really excellent indicator. You will understand what happens if you use it. Furthermore, with the information processing system, the data at the time of purchase are accumulated, and the technical index values at the time of sale are also recorded.If a large amount of data is accumulated, the RSI is 20% or less. You can expect a special effect that you can understand the success rate when you can purchase it and the success rate when you sell it at 80% or more. The difference in results between short-term trading and medium- to long-term trading is also clear.

(Action of trading data subject to aggregation by technical index)
The information generation unit 3021 includes the data of the technical index in the purchase data and the sale data. For example, an RSI index column is provided. This technical indicator column may be multiple, may be single, or another table (technical indicator table, etc.) may be used. To explain the operation in the case where one of the simplest RSI index columns is provided, the RSI value is entered in the purchase data and the sale data. The purchase data is managed as the purchase brand, purchase date, purchase market price, and RSI value. Once the brand, purchase date, and market price are determined, it will be calculated by the information processing system, so it may be calculated later or immediately. It can be automatic or manual.

Among the purchase data, it is possible to obtain the success rate of the combination of the purchase data having an RSI of 20% or less and the sale data having an RSI of 20% or more.

(Effect of trading data subject to aggregation by technical index)
Explaining the effect with the previous example, only the trading data composed of the purchase data with RSI of 20% or less and the sale data with RSI of 80% or more is extracted (RSI 20% or less at the time of purchase and RSI 80% or more at the time of sale). By doing so, the trading data to be aggregated by technical index is created.

Special effects such as being able to aggregate the trading profit / loss ratio of this aggregated trading data and verify whether or not it is different from the trading profit / loss ratio calculated by the information processing system. Can be expected. It can also be used to judge the quality of technical indicators from actual trading data, and if this technical indicator becomes like this, it will be possible to obtain knowledge that the probability of success is high, and by incorporating it into AI etc., the current probability of success is high. With this, the buying brand can be expected to display the success probability as%, and various effects can be expected.

(Specific examples of trading data subject to aggregation by technical index)
In addition to the above-mentioned specific examples, there are the following specific examples.

(Specific example 1)
It is possible to include the foot that appeared in the candlestick in the data. By managing the shape of candlesticks, such as the Taiyo line and the Taiyo line, in the purchase data, it becomes clear what the average trading profit / loss ratio of the stocks purchased at the time of the Taiyo line is. Since the amount of information is very large and complicated, it is more realistic to manage it in a separate table.

(Specific example 2)
For example, if a person who bought in a certain range and sold in a certain range in Stochastic Oscillator has a high probability of success and a high rate of return on trading, the stock at the time of buying according to this rule is currently this stock. The answer is possible. If you purchase this brand in this range, you can display the probability of success by what percentage. In addition, if the stocks held are in the range where the probability of successful sale of Stochastic Oscillator is high, it will be possible to add functions such as telling it.

(Specific example 3)
For example, whether or not the purchase judgment index with the Ichimoku Kinko Hyo is lit is managed in the ● × format, and the winning rate and trading profit / loss ratio of the trading data to be aggregated by the technical index of ● are classified by the technical index of ×. It is also possible to compare with the trading data to be aggregated. Since the actual trading data is used, it is possible to confirm the success or failure of all technical indicators.

(Specific example 4)
By importing a number of technical indicators into the database and linking them with trading data, the combination of the numerical values of the technical indicators with the highest probability of success will come out. When the RSI is 20% or less and the 25-day moving average deviation rate is what percentage or less, it is possible to estimate the probability of successful purchase. In this case, the larger the amount of data, the more room for separate table management and AI to play an active role.

(Specific example 5)
It is also useful to create trading data to be aggregated by technical index for article data such as a number of technical indicators and how much profit can be obtained with this technical index.

(Specific example 6)
The method of incorporating the technical index value into the trading data in the trading data to be aggregated by investor is called the trading data to be aggregated by investor by technical index. By linking the purchase data and sale data of trading data with the technical index value on the axis of an investor, it is possible to show the recent trading behavior of other stocks when making a purchase decision.

(Specific example 7)
The method of incorporating the technical index value into the trading data in the trading data to be aggregated by investment target is called the trading data to be aggregated by investment target by technical index. By linking the purchase data and sale data of trading data with the technical index value on the axis of investment target, it is possible to show the recent trading behavior of other investors when deciding to purchase the A brand.

(Old method of trading data subject to aggregation by profit and loss)
In the first and second embodiments, there are explanations regarding the evaluation of various profits and losses. Further, in the first embodiment, there is an explanation of acquiring various profit / loss totals from the trading data. These are used in the process of calculating the evaluation index, and are required in the step performed after the step of creating the trading data to be aggregated by profit and loss this time.

(Differences between trading data subject to aggregation by profit and loss and the old method)
FIG. 30 is a diagram for explaining the difference between the profit / loss aggregated trading data and the profit / loss level trading data according to the present embodiment.

FIG. 31 is a diagram showing at which step each of the profit / loss aggregation target trading data and the profit / loss level trading data is used.

In the step of creating the trading data to be aggregated by profit and loss, the step is to extract only the trading data that has been counter-traded and confirmed from the trading data. In the extraction that creates another trading data from the trading data, it is extracted and processed trading data because it is extracted by the profit and loss according to the purpose.

(Definition of trading data subject to aggregation by profit and loss)
There are various types of profit and loss calculated from trading data. In addition to unrealized profit, unrealized loss, trading profit, trading loss, trading profit / loss, unrealized profit / loss, total profit / loss, etc. can be raised. For example, when the trading data is extracted at the unrealized profit level, the trading data that is unopposed trading and has a profit is defined as the trading data to be aggregated by profit / loss extracted at the unrealized profit level.

(Issues of trading data subject to aggregation by profit and loss)
Since the purpose of buying and selling investment products is mainly to improve profit and loss, it is important to extract trading data based on the target profit and loss. The purpose of the first embodiment is to calculate the evaluation index, while the purpose of the step of creating the trading data to be aggregated by profit and loss according to the present embodiment is to narrow down the target to be evaluated.

(Action of trading data subject to aggregation by profit and loss)
The information generation unit 3021 extracts trading data at the profit / loss level and creates trading data to be aggregated by profit / loss. For example, if the aggregation target is a trading profit / loss, the information generation unit 3021 extracts only the confirmed counter-trading trading data. At this time, when the trading data is created, the non-reverse trading data and the counter-trading data are processed, and the case where the table is linked to the market price and the case where the trading data is not linked are slightly different. In the case where the market price is linked to the market price in the table, the unreversed trading data is easy to handle because the market price is updated along with the update of the table data for each issue. On the other hand, if the market price is managed by item, it will be difficult to manage, so it is desirable that the market price is linked to this profit / loss-specific trading data by a table type or a method close to it.

(Effect of trading data subject to aggregation by profit and loss)
By specifying only the extracted trading data for the target profit and loss, it is possible to evaluate only the trading data with the trading profit. As a result, the trading profit margin of Mr. A's A brand, the trading profit margin of Mr. B's B brand, etc. can be seen side by side, which has the effect of enabling appropriate evaluation.

(Issues of automatic creation of trading data to be aggregated)
The information that users are looking for is diverse. Depending on the user, you want a trading profit ranking by brand, you want to know what the total profit / loss ratio of all investors is, and what is inferior to those who are good at buying and selling. I want to know, and I have various needs.

The procedure for creating the trading data to be aggregated differs for each of these. It would be convenient to be able to create aggregated trading data according to the needs, rather than satisfying all the needs from the beginning. For that, it is necessary to automate the creation of trading data to be aggregated.

(Action of automatic creation of trading data to be aggregated)
After deciding what you want to know according to the request of the user or administrator, the criteria for creating the trading data to be aggregated is decided. For example, for the issue of what is the stock with the highest winning profit margin in 2020, the trading data subject to aggregation by period in 2020 is suitable. If you can get what you want to know by filling out a questionnaire, input form, selecting from options, etc., specify the necessary trading data to be aggregated. Alternatively, it also includes presenting an issue from the beginning and automatically creating aggregated trading data that matches the issue.

By deciding what data is required, what kind of aggregation method, what kind of classification method, and what kind of extraction method should be used to create trading data in order to realize this issue, the creation of trading data to be aggregated is automated. Is possible.

For the issue of what is the stock with the highest winning profit margin in 2020, it is important to automatically create the trading data to be aggregated for each period in 2020. You can use AI or refer to a table. The profit / loss level trading data is the winning profit level, and the purpose is to calculate the winning profit ratio by aggregating the trading data with the winning profit for each issue and the winning purchase price in the trading data for each component. Trading data is obtained.

These automatic creations may use AI or refer to a table.

When referring to the table, it is necessary to correspond in advance to which aggregation target trading data should be created or which aggregation target trading data should be created for various issues. The same applies to the third and subsequent steps below. In the above example, the issue of what is the stock with the highest winning profit margin in 2020 is the table. In the creation of level trading data, the winning profit level trading data is created and the procedure for creating it, and the third step is the trading data for each component. If you can refer to them in the table by the profit margin, it will be possible to automatically create them programmatically accordingly. Neither step is mandatory, and in some cases it is not necessary.

As the data structure of this table, the vertical axis shows the type of trading data to be aggregated, the aggregation of the trading data, the classification extraction aggregation method, the type of profit / loss level trading data, the extraction method, the type of trading data by component, and the components. It has items such as how to create whether to aggregate or extract separately, the type of evaluation index, calculation method, etc., and by setting the issue on the horizontal axis, create the target trading data and evaluation index for the issue. Is possible.

You may let them learn and answer various tasks. In addition, a table may be used, and the format such as a correspondence table does not matter. You can also increase or decrease these items. The horizontal axis described above may include any one, may include a plurality, or may include another standard. For example, once the type is decided, there is a work table of that type, and the work table may be used to decide what kind of processing, extraction, aggregation, etc. should be performed. It is a method to automate what kind of trading data is created and how to create it for the problem.

(Effect of automatic creation of trading data to be aggregated)
It's relatively easy to decide what you want to do, but it's difficult to decide which trading data to use. By deciding what you want to do, calculating back from it, determining the necessary trading data to be aggregated, and automatically creating it, there is a special effect that anyone can use it.

(Specific example of automatic creation of trading data to be aggregated)
(Specific example 1)
For example, for the issue of what is the stock with the highest winning profit margin in 2020, the trading data subject to aggregation by period in 2020 is suitable.

(Specific example 2)
If it is the best 10 of the stocks whose trading profit is increasing in 2020, the component trading data will be classified by stock in the trading data to be aggregated by period in 2020.

(Specific example 3)
If you want to know what index you are inferior to the average, you can use the total profit / loss level trading data in Investor A and the component trading data of all investors in the aggregated trading data of all investors. It can be achieved by creating (even if you have it in the previous process).

(Specific example 4)
If you want to know whether the total profit / loss has increased or decreased by comparing 2020 and 2019, you can use the component trading data by year in the aggregated trading data of all investors. Total P & L level This can be achieved by using trading data.

(Specific example 5)
If you want to know which is better, the result of the person with a high winning rate in 2020 (70% or more) or the result of a person with a high winning profit rate in 2020 (20% or more), the trading subject to aggregation by period in 2020 Investor-specific component trading data is created from the data, profit / loss level trading data is created using the information processing system (it is possible to have it in the previous process), and the winning rate and the winning profit margin are used as evaluation indexes to win the winning rate. It is obtained by aggregating the total profit and loss ratios of Group A with a winning profit margin of 70% or more and Group B with a winning profit margin of 20% or more.

Necessary trading data can be extracted by deciding which trading data to be aggregated, which component trading data to use, which profit / loss level trading data to use, and which evaluation index to use for various issues. Alternatively, it is the step of automatically creating trading data that can be classified, aggregated, and processed to solve the problem, and the step of automatically creating the trading data to be aggregated is the step.

After creating these aggregated trading data, the process of creating trading data for each component is performed.

The first step is the acquisition step of trading data. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component (this step), and is possible even after the fourth step. The fourth step is the step of creating profit / loss level trading data (even after the second step). The fifth step is the calculation step of the evaluation index.

(Step of creating component trading data)
In the component trading data creation step, the information generation unit 3021 uses the aggregated trading data created in the first step (when the profit / loss level trading data is created first, after the profit / loss level trading data is created) for a period. It is displayed by dividing or extracting by, by investor, by investment target, by profit or loss, by investment type, by adviser, by securities company, by medium, etc. It is defined as component trading data to classify and aggregate and extract this aggregated trading data (trading data that has passed the first stage) or profit / loss level trading data (trading data that has passed the first stage and the third stage) for each component. ..

Mr. A's aggregated trading data (aggregated trading data by investor) can be classified into component trading data by period in 2019 and 2020. In this case, by extracting and creating the trading data in which Mr. A invested based on the investor named Mr. A, and extracting the trading data to be aggregated and the trading data for 2019 by period, 2019 Component trading data can be created. You may first go through the third step, convert the trading profit / loss level into trading data, and go through this step (in the order of the first step, the third step, and the second step). This is defined as Mr. A's 2019 component trading data (in the latter case, Mr. A's 2019 trading profit / loss level trading data). It also includes aggregating the data for 2019 and aggregating the data for 2020. For example, the trading profit / loss level trading data of Mr. A is aggregated for each issue and included in the definition of this component trading data such as the total value of the A issue and the combined value of the B issue. This is a case of summing up in one table, but create separate tables, and the trading data of Mr. A's trading profit / loss level, like the trading data of Mr. A's A brand and the trading data of Mr. A's B brand. Also include division.

The aggregated trading data of the A issue (aggregated trading data by investment target) is divided into component trading data for each investor such as Mr. A and Mr. B. In this case, trading data in which stock A is invested is extracted and created based on the investment target of stock A, and the trading data to be aggregated is further extracted (or only the trading data of Mr. A by investor). By performing another aggregation), the component trading data of Mr. A and Mr. B of the A brand can be created. Here, it is also possible to create trading data of trading profit / loss level first and create trading data of Mr. A for each investor (in this case, it is defined as trading data of trading profit / loss level of Mr. A of brand A). ). This is defined as the component trading data of Mr. A of the A brand.

It is also possible to further divide the component trading data such as by period, investor, investment type, medium, securities company, and investment target by component. For example, it is possible to nest the aggregated trading data of Mr. A by year and further classify by brand. In this case, Mr. A's results by brand in 2020 and results by brand in 2019 can be obtained. Furthermore, it is possible even after the trading data to be aggregated (first step, second step, third step) and after creating the profit and loss level trading data (first step, third step, second step). be.

(Relationship with the old method of component trading data creation step)
The old method of understanding the trading data is to collect the trading data in a lump, and the new method makes it clearer what purpose and what kind of target is to be extracted, so that the target of work is A wider and deeper analysis is possible. There are elements that make up the trading data to be aggregated, for example, stocks, investors, securities companies, technical index values, etc., extracted based on those components. It is this component trading data that is reclassified, reclassified, and reaggregated.

(Significance of component trading data creation step)
In the step of creating component trading data of the new method, what criteria (whether by investment, investment target, period, etc.) should be used to extract and aggregate the trading data to be aggregated, and what (aggregation target). , A brand or B brand) is clarified. By omitting this step from the trading data to be aggregated, the profit / loss level trading data is created by the information processing system of the next step (it may be held in the previous process), and the profit / loss level trading data is also used as a standard (in the same way). It is also possible to extract and aggregate by investment, investment target, period, etc.). Depending on the task, this step itself may be skipped.

(Issues in the step of creating component trading data)
By further narrowing down the trading data to be aggregated or the profit / loss level trading data (the process after the trading data to be aggregated), or by taking steps to aggregate by component, the nature of the evaluation target becomes clearer, and the nature of the evaluation target becomes clearer in 2019. It becomes easy to compare and rank the trading status of the S company stock and the trading status of the P company stock. It is easy to calculate the evaluation index by itself to evaluate the data to be aggregated for each period in 2019, which is defined as the data to be aggregated, but as a further breakdown of 2019, Mr. A's How does the trading data (or aggregated data) compare with the trading data (or aggregated data) of investor B, and how is the profit margin calculated from the trading data of issue A compared to other issues? In addition, it will be easier to evaluate by providing a further breakdown of components such as ranking of winning rates calculated from the trading data of A securities company. It will be easier to compare and rank. Profit and loss level trading data is created by the information processing system first from the trading data to be aggregated (it is possible to have it in the previous process), and the profit and loss level trading data is also used according to which standard (investment target). It is also possible to extract and aggregate by (whether it is different or by period, etc.).

By dividing and aggregating the basic evaluation targets (aggregation target and profit / loss level trading data) by components such as period, investor, investment type, medium, securities company, investment target, etc. Furthermore, it becomes possible to know the nature of trading data.

(Action of component trading data creation step)
Creation of component trading data by dividing the trading data to be aggregated (or the above-mentioned profit / loss level trading data) into components such as by period, by investor, by investment type, by medium, by securities company, and by investment target. Is possible. Various combinations are possible, and by calculating the evaluation index for each issue of the investment type day trading type aggregated trading data, it becomes clear what kind of issue the day trading type people are winning or losing. By delivering this kind of information to many people, we can expect the effect of significantly changing investment behavior.

(Effect of component trading data creation step)
The trading data to be aggregated (or the above-mentioned profit / loss level trading data) is further divided into components such as by period, by investor, by investment type, by medium, by securities company, and by investment target. By creating it, it becomes possible to calculate the winning rate and trading profit / loss of the A issue for each year. It will be easier to create articles such as how profitable everyone is in 2020 and 2019 for S company stock. By calculating multiple evaluation indexes from multiple perspectives, it becomes easier to evaluate, and it is possible to make comparisons by year, rank the results of each year, and make diagnoses and advice based on the results. It is difficult to process trading data in this nested relationship by a method other than the database, and the information processing system uses the trading data to be aggregated by investment target for the winning rate and trading profit / loss of issue A in FY2020. In addition, the winning rate and trading profit / loss in 2019 are calculated by the information processing system, and there is no choice but to do it in 2018, but in this case, it is very difficult to obtain rankings. However, since it is not impossible, it is a form of creating component trading data here, including these methods. The same applies to component rankings and the like.

(The first step of automatic creation in the step of trading data to be aggregated)
The automatically created trading data to be aggregated may be selected by the administrator or decided by the user, and a form is used to ask what he / she wants to do (for example, the trading profit ranking of stocks in 2020). , You may decide the trading data to be aggregated by it.

Automatic creation step of aggregation target trading data of form input method, automatic creation step of aggregation target trading data of questionnaire input method, automatic creation step of aggregation target trading data of selection method, automatic creation step of aggregation target trading data of pull-down selection method and so on.

Let the administrator or the user decide what he / she wants to do, such as whether to use form input, questionnaire input, selection method, etc., and what he / she wants to do. Will automate the creation of aggregated trading data. You may or may not use AI. If AI is not used, the type of what you want to do is decided in advance, and in this case, the trading data to be aggregated is created under such aggregate extraction conditions. It goes through a creation process such as creating trading data.

In the case of form input or questionnaire input, what you want to do is finally decided, so the trading data to be aggregated is automatically created according to the decided.

In this case, it is possible to improve the accuracy by having AI learn how to do it by machine learning or the like.

(Significance of automatic creation in the steps after the trading data to be aggregated)
Once the issue (what you want to do) is decided, not only the trading data to be aggregated but also the trading data by component can be created, the type of profit / loss level trading data and evaluation index is decided, the creation procedure is decided, and it can be created automatically. It is possible to decide which trading data to use (type of trading data), what (which profit / loss), how (which evaluation index to use), and how to improve.

The automatic creation of the component trading data and the automatic creation of the profit / loss level trading data are created by the same procedure as the procedure for automatically creating the aggregation target trading data described above. As described above, by replacing the aggregated trading data that describes the actions, issues, effects, specific examples, etc. with trading data by component or profit / loss level trading data, almost automatic creation becomes possible. Differences from the trading data to be aggregated will be explained as needed.

By going through these three trading data creation procedures, the target profit / loss (or average trading profit / loss ratio (ROI average)) and the target trading data (aggregated trading data (first step, second step, or first step) (Created in 3 steps), trading data by component (created in 1st step, 2nd step, or 3rd step), profit / loss level trading data (created in 1st step, 2nd step, or 3rd step) Etc.) is decided.

A specific example is shown below.

(Specific example 1)
For example, for the issue of what is the stock with the highest winning profit margin in 2020, the trading data subject to aggregation by period in 2020, the winning profit level trading data, and the trading data by component of the stock are available. Are suitable.

(Specific example 2)
If the issue is what is the best 10 of the stocks with high trading profit / loss in 2020 (stocks that everyone earns), the trading data to be aggregated by period in 2020, the trading profit / loss level trading data, and the component trading data. However, the evaluation index is ranked by trading profit and loss.

(Specific example 3)
If you want to know what indicators you are inferior to the average, you can use the aggregated trading data for all investors, the component trading data for Investor A and all investors, and the total profit and loss level trading data. (It is possible to have it in the previous process), and by calculating the evaluation index that affects the total profit and loss, it is possible to give an answer.

(Specific example 4)
If you want to know whether the total profit / loss has increased or decreased by comparing 2020 and 2019, you can use the aggregated trading data of all investors, which is the component trading data for each year. It can be achieved by using the total profit / loss level trading data.

(Specific example 5)
If you want to know which one is profitable, the result of the person with a high winning rate in 2020 (70% or more) or the result of a person with a high winning profit rate in 2020 (20% or more), it is subject to aggregation by period in 2020. Investor-specific component trading data is created from trading data, profit and loss level trading data is created by the information processing system (it may be held in the previous process), and the winning rate and the winning profit rate are used as evaluation indexes. It is obtained by totaling and comparing the total profit / loss ratios of Group A with a winning rate of 70% or more and Group B with a winning profit rate of 20% or more.

(Specific example 6)
Component trading data can also be used for article data such as popular foreign stocks and which foreign stocks are successful, and creation of article data on numerous investment products and which investment products will be successful in 2020. In addition, it is useful to create the trading data to be aggregated by investor.

(Specific example 7)
The specific example shown in Fig. 101 is the stage of evaluating investor A in the stock A and stocks in 2019, and the profit and loss level of the target extracted by its components and further narrowed down. According to this diagram, various conditions can be set, and once the conditions are set, they can be imported by a method such as table reference.

The creation method by trading data extraction processing of each profit / loss level is as follows.

The first step is the acquisition step of trading data. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component (even after the fourth step). The fourth step is the step of creating profit / loss level trading data (this step) (even after the second step). The fifth step is the calculation step of the evaluation index.

(Definition of step to create profit / loss level trading data)
In the information processing system, in order to determine the target for processing the trading data, the trading data to be aggregated is created in the second step, and the components of the target are extracted (or classified, aggregated, processed) in the third step. Determine the target profit and loss, and create the profit and loss level trading data in the fourth step. This fourth step may be performed before the creation of the trading data to be aggregated, but considering the subsequent process, it is possible to respond more flexibly by performing this step in this order.

(Problems of conventional technology)
Even in the first embodiment, as described in "Acquiring basic data from the acquired trading data and calculating the evaluation index by referring to the acquired basic data", the evaluation index is calculated by referring to the basic data. , Embodiment 4 takes the above-mentioned second step, third step, and fourth step, and then calculates an evaluation index. The fourth embodiment is premised on database linkage, and can handle big data sufficiently. The former is premised on individual trading data and does not assume handling big data. The first embodiment is a method of calculating an evaluation index assuming an investor A of the investor aggregation target trading data in the fourth embodiment, and the fourth embodiment is an investment target aggregation target trading data and a period-specific aggregation target trading data. It is possible to handle concepts that are not expected in Embodiment 1, such as, and technological innovation so that evaluation indexes can be calculated in cooperation with the database, and centralized management and integrated management can be performed, including the use of the calculated evaluation indexes. This is the invention of the fourth embodiment. This step also plays an important role in it. Profit and loss determination and trading data to be worked on (working target trading data) are created in this step. It is a very important and indispensable process because the evaluation index is calculated from the work target trading data. However, it is assumed that it will be brought after the acquisition of trading data, but in the 4th step, the target is already decided in the 2nd step, so the profit and loss level of the target can be changed according to the situation. , Applicable. After deciding the target to be evaluated (second step and third step), it is the process that is responsible for the profit and loss (fourth step) to evaluate the target to be evaluated.

(Action of step to create profit / loss level trading data)
Up to the third step, "what" of what to evaluate was decided. For example, "Mr. A's trading data", "SoftBank stock trading data", "2020 stock trading data", etc., the contents of which are determined by extraction conditions, classification conditions, aggregation rules, etc. The step is a step to decide which profit / loss of those targets should be evaluated. There are various purposes for investment, but the ultimate goal is to achieve good results. In other words, one of the important purposes is to improve the investment profit / loss (return on investment ROI). There are many types of investment gains and losses, which is an important purpose. The step is to decide the level of profit and loss to be improved, including trading profit and loss, unrealized profit and loss, with total profit and loss at the top. How to extract (or classify, aggregate, process) trading data is determined by which level is targeted, which is divided into four levels. The method is described in detail in the following paragraphs.

(Effect of step to create profit / loss level trading data)
Although the technology is a leap compared to the first embodiment, various operations are performed in the information processing system that is consistent from the second step to the twelfth step, and all the steps play a certain role. The point is that the technological evolution is particularly large. If this step is the process of determining the target profit / loss level and focuses on changing the status of the stocks held, was the unrealized profit / loss level trading data and various judgments of the past trading status wrong? If you want to get advice, such as whether it was correct, how to improve it, etc., the trading profit / loss level trading data is suitable, and anyway, the whole picture, including what you own and what you are buying and selling. , Total profit / loss level It is suitable to create trading data. By this creation, the type of evaluation index that can be calculated by the information processing system will be decided in the next step, and this decision will be effective from the subsequent evaluation, advice, and diagnosis, so it is a very important step.

(Specific example of the step of creating profit / loss level trading data)
Various specific examples are shown below.

(Profit and loss level trading data creation step)
The profit / loss level trading data includes the first level (total profit / loss level trading data), the second level (trading profit / loss level trading data and unrealized profit / loss level trading data), and the third level (winning profit (losing loss) level trading data and unrealized gain). (Unrealized loss) level There are four levels: trading data) and the fourth level (see below). It may be at a higher stage or at a lower stage. What is important is that the profit and loss of the hierarchy below the total profit and loss is a component of the total profit and loss.

In relation to profit and loss, the target profit and loss of the total profit and loss level trading data is the total profit and loss (or the total profit and loss ratio). Hereinafter, the same applies to the trading profit / loss level trading data, which is the trading profit / loss. As a relationship with the trading data, the total profit / loss level trading data is trading data including both the trading data held and the trading data already traded, and if it is only the trading data held, the unrealized profit / loss level trading data. It becomes.

In addition, the buying and selling data of counter-trading includes a set of buying and selling in the data, but in the non-counter-buying buying and selling, the selling data (or buying data) paired with the buying data (or selling data) is included. Since there is no data), the price data of the paired data includes the provisional inclusion of the market price and the current price at a certain point in time. There is a method of managing this point in a separate table (see FIG. 86).

In addition, there is a relationship of "total profit / loss = trading profit / loss + unrealized profit / loss" and "trading profit / loss = winning profit + losing loss", and the profit / loss of the lower layer is a component or influence factor of the total profit / loss. Hereinafter, the relationship between the second level and the third level is the same, and the relationship between the third level and the fourth level is also the same. As the level of the hierarchy gets deeper, detailed data can be obtained, and all profits and losses are linked to total profits and losses, and have a structure that is one of the components.

Therefore, if you want to increase the total profit and loss, if you improve the profit and loss at some level (if other conditions are constant), it will improve. Because of this structure, if you want to improve the total profit and loss, you can see the improvement measures by referring not only to the total profit and loss level but also to the profit and loss level trading data of the lower hierarchy.

(Old method of total profit / loss level trading data)
In the first embodiment, there is a description that "acquire the trading data of the investment product, and ... acquire the evaluation index related to the total profit / loss from the calculated evaluation index", and there is a description of the processing of the total profit / loss analysis. The types of evaluation indicators, diagnostic procedures, decomposition formulas, etc. are described.

Therefore, the information generation unit 3021 of the server 30 according to the fourth embodiment acquires the trading data of the investment product, extracts (or classifies, aggregates, and processes) the above-mentioned trading data for each standard, and creates the aggregated trading data. Using the aggregated trading data, trading profit / loss level trading data related to fixed profit / loss, unrealized profit / loss level trading data related to undetermined profit / loss, etc. are created according to the purpose, and trading profit / loss level trading data is used. The trading profit / loss level evaluation index for evaluating the trading profit / loss level is calculated, and the unrealized profit / loss level evaluation index for evaluating the unrealized profit / loss level is calculated from the unrealized profit / loss level trading data. Use the indicators to generate information about the valuation of the total profit and loss of investment products.

(Significance of total profit / loss level trading data)
FIG. 42 is a diagram calculated step by step from the profit / loss level trading data according to the present embodiment. FIG. 43 is a diagram showing a specific example of calculation of the profit / loss level stage evaluation index according to the present embodiment.

The total profit / loss is the amount of profit / loss generated as a result of trading, and the trading data created based on the trading data to be aggregated in order to evaluate the total profit / loss is defined as the total profit / loss level trading data. The first level in FIG. 42 is the total profit / loss, and the trading data thereof is the total value of the total profit / loss level in FIG. 43.

The total profit / loss includes the trading profit / loss whose profit / loss is fixed by the counter-trading and the unrealized profit / loss held by the non-counter-trading. For example, it refers to the total profit / loss obtained from an investment product, the total profit / loss obtained by an investor from an investment target, the total profit / loss in 2019, and the like. The total profit / loss level trading data includes all trading data to be aggregated.

(Issues of total profit / loss level trading data)
The starting point is the principal (or the valuation amount at the time of A), and as a result of buying and selling from there, the valuation amount of the currently owned products (or the valuation amount at the time of B) and how to evaluate the cash balance. Becomes an issue.

The old method described above is also one approach, but by processing the trading data to be aggregated and utilizing the created total profit / loss level trading data, it is more versatile and becomes the basis for calculating the evaluation index (Fig.). See 43).

A large number of profits and losses are included in the trading data to be aggregated, and the total profit and loss is the sum of these profits and losses. The trading data for evaluating this total profit / loss is defined as the total profit / loss level trading data.

Comprehensive P & L Level Trading data gives you an overall picture of your investment. For example, as shown in FIG. 43, even if the principal is 500,000 yen, the purchase price is 144.59 million yen, and it can be seen how the principal is rotated. The total profit / loss ratio is 15%, but the turnover is fully effective, and the total profit / loss of 22.3 million yen is obtained by using the purchase amount of 144.59 million yen. The trading data for evaluating the total profit / loss of the investment target, the investor's profit / loss, and the total profit / loss for each period is the total profit / loss level trading data.

(Action of total profit / loss level trading data)
Processing is required to obtain trading data for evaluating the total profit and loss. Of the aggregated trading data, the creation process differs depending on whether or not it is the aggregated trading data for each period.

If it is not the trading data subject to aggregation by period, the issue is how to evaluate the current holding product valuation amount and cash balance as a result of buying and selling from the principal at the start. Become.

Since it is the processing of trading data for evaluating the total profit and loss, it is necessary to evaluate the current (or the market price at the time of B) the remaining holdings as a result of buying and selling with the principal as the source. Therefore, the information generation unit 3021 creates the total profit / loss level trading data (may have it in the previous process) by including the B time point evaluation value of the owned product in the trading data. The information generation unit 3021 increases items such as the total profit / loss ratio and the holding period by processing.

If the trading data is subject to aggregation by period, revaluation is required. The issue is how to evaluate the current (or B) holding product valuation amount and cash balance as a result of buying and selling from the holding product valuation amount and cash balance at the start point A. Become.

The trading data to be aggregated is processed as follows.

The information generation unit 3021 creates total profit / loss level trading data by revaluing the purchase unit price of the products held at the time A at the market price at the time A and revaluing the products held at the time B at the market price at the time B (previous process). You can bring it to).

Specifically, the information generation unit 3021 revalues the trading data purchased before the time A at the market price at the time A, and revalues the products that are still held at the time B at the market price at the time B. , Create total profit / loss level trading data (even if you have it in the previous process).

However, as a method of revaluation, there are a method of replacing the purchase date, the purchase unit price, and the purchase amount with the A o'clock, the A time point market price, and the A time point evaluation value, and the method of setting up another item.

In addition, items such as total profit / loss ratio, holding period, benchmark rise / fall rate, etc. may be added to the total profit / loss level trading data according to the purpose. Further, it may be totaled for each component item or the whole may be totaled.

(Effect of total profit / loss level trading data)
The total profit / loss level trading data is total, such as whether the investment target, the investor, or the trading and holding by period is causing a loss or making a profit as a whole, and how it is divided by a certain period. It is trading data for evaluation.

Investor A has been buying and selling variously over the past year, and as a result, whether his assets have increased or decreased, how many times he has bought and sold, how many stocks have been purchased, and what was the rate of increase / decrease in principal? In order to evaluate that, the information generation unit 3021 creates the total profit / loss level trading data (it may be held in the previous process).

By adding the profit / loss ratio as an item, the total profit / loss ratio of each trading data becomes clear. By extracting (or classifying, totaling or processing) with a component item called a stock code and extracting (or classifying, totaling or processing) trading data for each stock, the composition of each stock of total profit and loss becomes clear. You can easily create a list of total profit and loss for each investor and investment type.

(What is total profit / loss level trading data)
The second level separates the trading data and the unrealized trading data, while the first level collects all the trading data to be aggregated, including the data of counter-trading and the data held. It is totaling.

(Specific example of total profit / loss level trading data)
For example, if Mr. A's 2019 is to be evaluated, the trading data of 2019, the evaluation value of the products held at the start of the beginning of 2019, and the cash will be evaluated by various transactions at the end of 2019. How to evaluate the transition to trading data between the amount and the cash balance becomes important. The information generation unit 3021 creates comprehensive profit / loss level trading data by revaluing the stocks held at the beginning of the year at the market price at the beginning of the year and valuing the products held at the end of the year at the market price at the end of the year.

Specifically, the following processing is required. Based on the valuation amount at time B, the information generation unit 3021 evaluates the trading data of unopposed trading at the market price at time B in order to calculate the balance (it is better to evaluate in the first step and the second step). ). The information generation unit 3021 adds up the non-reverse trading data and the counter-trading data, and if the purchase date is before the A time point, revaluates at the A time point market price (see FIG. 23 and the like).

The method of revaluation is explained in detail in the section of trading data subject to aggregation by period. Further, as described above, there are two notation methods. In addition, items such as the total profit / loss ratio may be added.

(Definition of second level trading data)
The total profit / loss level trading data is divided into trading profit / loss level trading data in which profit / loss is confirmed by counter-trading and unrealized profit / loss level trading data in which profit / loss is undetermined in unreversed trading. It is defined as trading data (see the figure in which the total profit / loss of 22.3 million yen in FIG. 42 is branched into a trading profit / loss of 16.25 million yen and an unrealized profit / loss of 6.05 million yen).

(Old method of 2nd level trading data)
In the first embodiment, a method of calculating the trading profit / loss is described, and there is a description that the evaluation index calculation changes according to the level stage. In addition, there are evaluation indexes for trading profit and loss and basic numerical values. It describes the types of evaluation indicators, diagnostic procedures, decomposition formulas, etc., but does not describe how to extract and process trading data in order to evaluate trading profit and loss and unrealized profit and loss.
(Issues of Level 2 Trading Data)
In the total profit / loss level trading data, past results and current results are mixed, so only the whole picture can be understood. Which of the profit and loss you have and the profit and loss you bought and sold is more, whether both are profitable, whether the transaction you are buying or selling is profitable or lossy, and how long is the average trading period? I don't know what the winning percentage is.

By separating the trading data at the trading profit / loss level and the trading data at the unrealized profit / loss level, it is possible to evaluate the trading profit / loss and the unrealized profit / loss to be aggregated.

In addition, although the old method is a method of grasping by decomposition method etc., it is possible to create second level trading data by extracting and processing trading data, and by evaluating trading profit and loss and unrealized profit and loss based on this, it is possible to create second level trading data. You can expect different effects that take advantage of each characteristic.

(Second level means)
The information generation unit 3021 extracts (or classifies, aggregates, and aggregates) the trading profit / loss trading data that has already been confirmed by counter-trading and the undetermined unconfirmed trading profit / loss trading data that has not been counter-trading based on the trading data to be aggregated. Process) to create trading data.

Hereinafter, the case of processing the trading data subject to aggregation by period and the case of processing the trading data subject to aggregation will be described separately.

(In the case of processing of trading data subject to aggregation by period)
The information generation unit 3021 extracts the trading data having a purchase date or a sale date during the AB period, or the trading data held at the time B.

The information generation unit 3021 classifies the trading data having a purchase date during the AB period into trading profit / loss level trading data if there is a counter-trading during the AB period, and unrealized profit / loss level trading data if it is held at time B. (3 and 4 in FIG. 23).

The information generation unit 3021 performs revaluation at the market price at time A if the purchase date is before time A among the trading data having a sale date during the AB period (2 in FIG. 23), and if the data is held at time B. Is the market price at time A in the case of a purchase date before time A (1 in FIG. 23), and is evaluated with the purchase date as it is after that (4 in FIG. 23).

The information generation unit 3021 creates trading profit / loss trading data and unrealized profit / loss trading data by revaluing the investment product held at time A from the purchase market price to the market price at time A (a separate item may be set).

Specifically, the information generation unit 3021 revalues the product held at time A in the trading profit / loss trading data at the market price at time A, and revalues the product held at time A in the unrealized profit / loss trading data at the market price at time A. This is done by calculating the profit and loss of the trading data whose purchase date is before the time A in the trading data by changing it to the market price at the time A instead of the unit purchase price.

Here, if there is trading data at the time of B, it is easiest to create trading data to be aggregated by period. (See the section on aggregated trading data by period). Therefore, it is desirable to save the trading data in chronological order. In addition, the information generation unit 3021 may appropriately add items such as total trading profit / loss, winning profit, winning profit rate, and trading period to the trading data at the trading profit / loss level (create FIG. 33 based on FIG. 26), or configure items. By extracting, classifying, aggregating, and processing for each issue, period, and investor, the second level trading data suitable for the purpose is created.

The information generation unit 3021 appropriately adds items such as unrealized profit / loss total, unrealized profit, unrealized profit ratio, and holding period to the unrealized profit / loss level trading data, and extracts, classifies, and aggregates each of the constituent items such as stock, period, and investor. , Create second-level trading data that is more suitable for the purpose by processing. In addition to the above method, in addition to the above method, a set of valuation amount and trading data at time A, a set of valuation amount and trading data at time B, and trading data during the AB period are used to create trading data subject to aggregation by period. It can be created by combining them. This is also one of the methods for creating the above-mentioned period-specific aggregated trading data (see the four types of aggregated trading data).

(2nd level effect)
Based on the trading data that has already been confirmed by counter-trading (extracting only sold products in the case of purchased products) and the unconfirmed trading data that has not been counter-traded (extracting products that have not been sold in the case of purchased products). Then, processing is performed to create trading profit / loss trading data and unrealized profit / loss trading data.

In particular, it is very effective because it is often known at the second level when creating trading data subject to aggregation by period, trading data by component, and the like.

In the case of each period, the calculation of the old method calculation formula is complicated (it is almost impossible if the number of trading data is large), but according to this embodiment, by processing the trading data, it is further calculated. It is possible to easily create trading profit / loss trading data for each period with excellent listability and unrealized profit / loss trading data, which has the effect of facilitating the evaluation of the relevant period. Further, by adding items as appropriate, for example, the trading profit / loss ratio can be viewed for each trading data, so that an effect not found in the old method can be expected.

(Specific example of second level trading data)
FIG. 44 is a diagram showing a specific example of the second level trading data according to the present embodiment. For example, in the case of the 500,000 yen course shown in Fig. 44, a profit of 22.3 million yen was generated at the total profit / loss level, but the trading profit / loss can be decomposed into 16.25 million yen, the unrealized profit / loss can be decomposed into 6.05 million yen, and each period. It can be created according to various purposes such as extraction, classification, aggregation, processing, extraction, classification, aggregation, and processing for each brand.

(What is the second level trading data)
The third level separates the trading profit level trading data and the trading loss level trading data, while at the second level, the trading data in which the profit is confirmed by counter-trading is also the trading in which the loss is confirmed. The data is included in the total.

(Definition of trading data subject to aggregation by second level period)
It is defined as the second level period-specific aggregation target trading data that the information processing system creates the period-specific aggregation target trading data at the second level of profit / loss, which is the trading profit / loss level and the unrealized profit / loss level. I have occasionally touched on the difficulty of calculating the trading data subject to aggregation by period, but it is particularly difficult to generate this second level of period profit and loss. The first level profit / loss for a period can be easily obtained, but there is a problem that the second level trading profit / loss and unrealized profit / loss are not easy for each period. When the period is divided, the trading data that was the trading profit / loss becomes the unrealized profit / loss, the trading data that was the unrealized profit / loss becomes the trading profit / loss, the purchase price also needs to be revalued, and various work is done. It will be necessary, especially comparing past periods will be very difficult.

(Problems of conventional technology)
The reality is that it is difficult to compare portfolios in securities accounts, etc. by period. It is very difficult to understand how it was in 2020, how it was this month, etc., as it is expressed by the transition of the valuation amount. It is limited to the first-level valuation of total profit and loss, and the transition of the valuation amount is Sekiyama (details are mentioned in the period-specific aggregation target trading data of the aggregation target trading data). The transition is sufficient, and there are few problems because it is enough to know what happened to the valuation price rather than the details of the detailed trading. However, in the case of individual stock trading, various problems can be solved and the actual situation becomes clear by grasping at the second level. Therefore, for those who do individual stocks, an easy-to-understand period comparison is required.

(Action of trading data subject to aggregation by second level period)
Trading profit / loss level If the trading data is created first and the trading data to be aggregated by period is created by the information processing system, at first glance, it seems that the period comparison of trading profit / loss levels can be easily performed. However, as mentioned in the section of trading data subject to aggregation by period, when divided by period, there are movements such as trading profit / loss level trading data and unrealized profit / loss level trading data. This makes it difficult to correctly evaluate the period profit and loss. However, if the information processing system creates the trading data at the time of B in order to evaluate the buying and selling during the AB period, only the evaluation at the time of A needs to be changed, and the evaluation can be changed very easily. When the information processing system tries to create the trading data of the AB period with the trading data of the c time after the time of the B time, in addition to the revaluation of the AB time, the trading that occurred from the B time to the C time. Since it is necessary to correct the data, it will be a waste. Especially with big data, it becomes incomprehensible. Therefore, the first step is to store these trading data at point A, point B, and point C so that you can refer to them at any time, and secondly, the second level trading data at point B. Third, the trading data only for the AB period is extracted ((purchase time <A time and sale time> A time point) or purchase time> A time point), and fourth, based on the trading data at B time point. If only the evaluation change at the time A is the third step, these problems can be solved. It looks surprisingly easy, but it is a very difficult task that you can understand everything by repeating various trials and errors until you can do it in the end. Is.

(Effects and specific examples of trading data subject to aggregation by second level period)
The fact that the information processing system can create the second-level aggregated trading data by period is very effective in later processes, and various effects can be expected. For example, what is the average trading profit / loss ratio of SoftBank in 2020? Which stock has the highest trading profit / loss ratio in 2020? Article data including the results such as these can be easily generated by the information processing system. It is because of this second level that it is possible to compare the skill of buying and selling and the profit of the holder, and it becomes meaningful information only when the period can be divided such as 2020 and the period can be compared. By being able to compare the period at this second level profit and loss level, it is easy to compete and compare the skill of trading in the ranking, and it is also possible to accurately compare the investment results of medium- to long-term investment and short-term trading. It can be expected that various contents will be born. The effect of linking the second-level trading data with the trading data subject to aggregation by period, which was the biggest bottleneck in investor evaluation, is enormous.

(Definition of trading data by second level component)
What does it mean to create trading data by component based on the second level trading data? For example, it is possible to verify again from various angles based on the trading profit / loss level trading data (data on which trading is completed). The components in the trading data to be aggregated, that is, the brand, the period, the technical analysis, the corporate performance, etc. Is bad, and you can see where to improve. For example, if you create trading profit / loss level trading data from trading data by component of the trading data to be aggregated by investor (Investor A), Mr. A wins and loses in which stock. It becomes clear.

(Problems of conventional technology)
Past trading history is usually buried and verification does not proceed. The PDCA cycle of investment results does not turn around. However, if you create and utilize this second-level component-specific trading data, you will be able to see various issues and discoveries, and you will be able to see the path for improvement.

(Action of trading data by second level component)
Trading profit / loss level Trading data is based on the components, for example, the group with the latest increase in sales of 0-10%, the group with the latest increase in sales of 10% -30%, and the group with the latest increase in sales of 30% -2 times. If you divide into groups with the latest increase in sales of 2 times or more and aggregate by issue, you can see at a glance the issues of the group of 2 times or more and the issues of the 0-10% group, and you can see at a glance what kind of trading each has done. You can see with. By extracting (or classifying, aggregating, processing) trading data and further extracting (or classifying, summarizing, processing) the extracted (or classified, aggregated, processed) trading data by components, trading by component is performed. It is possible to create data and capture trading data based on corporate performance. The same applies to unrealized profit / loss level trading data. Now, everyone can expect the effect of making it clear at a glance what brand has unrealized gains and what brand has unrealized losses, and the effect that various articles and data that create attractive contents can be generated by the information processing system. Can be expected.

(Effect of trading data by second level component)
Since the trading data for each component is further divided into the trading data to be aggregated and the trading data is grasped, there is an effect that the trading data can be viewed from various angles. For example, what is the 2020 trading profit / loss ratio for SoftBank shares? Rather than the answer, what is the trading profit / loss ratio of SoftBank stocks by investment type (short-term trading group and medium- to long-term investment group) in 2020? Will have more detailed analysis and more users will be interested. This is the effect of linking the component trading data and the second level profit / loss level trading data. It enables deeper analysis such as single and double than the trading data to be aggregated.

(Specific example of trading data by second level component)
Since there are cuts for each component, for example, it is the simplest case to aggregate the investment results of Mr. A for each issue, but even in this simple case, any issue will lose money in buying and selling. You can tell whether you are making a profit, whether you are making a profit, the rate of return, the profit composition ratio, etc. in one shot.

(Definition of trading data subject to aggregation by second-level investment target.)
This second level is obtained by reconsidering the trading data to be aggregated by investment target with the trading data at the trading profit / loss level. For example, if you compare the investment target of stocks and the investment target of virtual currencies at the trading profit / loss level, it is possible to compare which one has a longer holding period and a higher profit margin, and what is the winning percentage. However, it becomes more and more clear at the first level which one has the unrealized profit. People who are making a profit on the A brand will be able to understand whether they are making a profit by buying and selling, whether they are holding it and making a profit, and which one is more profitable.

(Problems of conventional technology)
For example, how many people buy and sell stocks of company S, how much profits they make, how much they buy on average, and how much unrealized profits they have. Although it has not been released to the world at all, the information processing system can immediately derive an answer if it is the trading data subject to aggregation by the second level investment target. It is important to look at this second level in order to see whether the profit is increasing by buying and selling, or whether the profit is increasing by holding it. What I couldn't see at the time of the total profit and loss expands my horizons at once. Looking at the total profit and loss, it is difficult to understand the results of investment products. This is because buying and selling and holding are not separated. However, in reality, some people buy and sell investment products frequently and succeed, some people succeed in holding them, and vice versa. Some people can't move because of unrealized losses. In order to correctly evaluate and look at these, it is very important to look at the investment target products at the second level.

(Action of trading data by second level investment target)
Trading profit / loss level Trading data may be created first and the information processing system may create the trading data to be aggregated by investment target, or the trading data to be aggregated by investment target may be created first and the trading profit / loss level trading data may be created. It may be created by an information processing system.

(Effect of trading data by second level investment target)
For example, by creating trading data to be aggregated by investment target with "extraction condition: issue = SoftBank stock" and creating trading data at trading profit / loss level and trading data at unrealized profit / loss level, the trading data to be aggregated by second level investment target can be created. Can be created. As a result, the various evaluation indexes calculated by the information processing system have the effect of being able to calculate an evaluation index that can answer all the questions of the SoftBank stock.
(Specific example of trading data by second level investment target)
There are many specific examples. For example, it is possible to divide the winning percentage of stocks into stocks with a high winning percentage, stocks with a low winning percentage, and the like, and create data generated by the information processing system. These may be added to diagnostic materials and brand information, and can be used in various ways, including ranking and comparison.

(For each of the 2nd level trading data)
(Old method of trading profit / loss level trading data)
In the first embodiment, there is a description that the calculation method of the trading profit / loss and the calculation of the evaluation index change according to the level stage. In addition, there are descriptions of evaluation indicators and basic figures for trading profit and loss. The types of evaluation indicators, diagnostic procedures, decomposition formulas, etc. are described.

(Problems of trading profit / loss level trading data)
Trading profit / loss level Trading data can be used to evaluate trading profit / loss. The old method is a method of grasping by decomposition method etc., but it is possible to create trading profit / loss level trading data by extracting (or classifying, tabulating, processing) the trading data to be aggregated, and based on this, the trading status at the trading profit / loss level to be aggregated. To evaluate. FIG. 45 is a diagram showing a specific example of the second level (trading profit / loss level trading data) according to the present embodiment. FIG. 46 is a diagram showing a specific example of the second level (unrealized profit / loss level) according to the present embodiment.

(Means of trading profit / loss level trading data)
The information generation unit 3021 extracts and processes the trading profit / loss trading data that has already been determined by counter-trading based on the trading data to be aggregated, and creates the trading data.

In the processing of the trading data subject to aggregation by period, the information generation unit 3021 creates trading profit / loss trading data by revaluing the investment products held at time A from the market price at the time of purchase to the market price at time A. Specifically, the products held at time A in the trading profit / loss trading data are revalued at the market price at time A. In addition, the information generation unit 3021 calculates the number of rotations, the number of rotation days, etc. of the trading issue together with the principal by totaling the total values.

(Effect of trading profit / loss level trading data)
Taking the effect of the trading data subject to aggregation by period as an example, in the case of each period, the calculation by the conventional calculation formula method is a complicated calculation, but by processing the trading data, it is easier by period. Trading profit / loss level Trading data can be created, which has the effect of facilitating the evaluation of the relevant period. Furthermore, although it is difficult to aggregate and evaluate each trading data with the old method, it is very easy to do with trading data at the trading profit / loss level. In addition, by associating the stock price table with the stocks in the trading data by the method shown in Fig. 86, the market price update information of the stocks is updated even for the trading that has been sold sequentially, and not only the influence on the unrealized profit / loss level trading data but also , It also has a special effect at the 4th level, which will be mentioned later. In particular, if the process of creating the modified trading data table is performed in the first step, this process becomes even easier.

(What is trading profit / loss level trading data)
In the third level, the winning profit data and the losing loss data are separated, while in the second level, the winning profit data and the losing loss data are added up, so that the trading data of the entire trading profit and loss is collected. Is created to evaluate the overall picture of the trading status to be aggregated.

(Significance of unrealized profit / loss level trading data)
The total profit / loss level is divided into trading profit / loss trading data in which profit / loss is confirmed by counter-trading and unconfirmed unrealized gain / loss level trading data in unreversed trading. Handle data. Again, if you manage the table separately by market price as mentioned above, it is easier to update daily, you can easily get time series data, etc., and you can also make a graph such as changes in the valuation price of the stocks you own. The effect of being easy can be expected. Furthermore, the effect will be great if the unrealized profit / loss level trading data is created in a timely manner to be aggregated for each period. It can be expected to have the effect of making it possible to understand the actual situation of the stocks held. The unrealized gain / loss in 2019 increased, but the unrealized loss increased in 2020 (if it decreases compared to the end of 2019, it becomes an unrealized loss by period), rather than just the unrealized gain / loss or the unrealized gain / loss ratio. Even with the same unrealized gain evaluation, it is possible to make a deep evaluation, which is extremely effective in grasping the actual situation. In addition to stock price data, linking stock information and stocks with dates produces various effects. In particular, if the stock information of the trading data to be aggregated by investment target is linked in the stock table, the stock information and the trading data will be directly linked, it will be easier to manage, and the relationship between trading and stock will be understood more deeply. Can be expected. Furthermore, in the case of stocks and dates, various effects can be produced by associating performance trends and technical indicators with purchase data (described later). In particular, by linking stock information etc. with this unrealized profit / loss level trading data, it is expected that information on holding stocks will be easier to enter immediately, and it will be easier to react when the trends of holding stocks change. can.

(Issues of unrealized profit / loss level trading data)
Unrealized gains / losses can be evaluated for unrealized gains / losses. The existing technology is a method of grasping by a decomposition method, but the unrealized profit / loss level trading data can be created by extracting and processing the trading data, and the unrealized profit / loss is evaluated based on this.

(Means of unrealized profit / loss level trading data)
The information generation unit 3021 extracts (or classifies, aggregates, and processes) undetermined trading data that has not yet been counter-traded based on the aggregated trading data, and creates unrealized profit / loss level trading data.

The information generation unit 3021 creates unrealized profit / loss trading data by revaluing the investment products held at time A from the market price at the time of purchase to the market price at time A in the processing in the case of the trading data subject to aggregation by period.

Specifically, in the unrealized profit / loss trading data, the unit price of the products held at the time B and the purchase date before the time A is revalued at the market price at the time A. In addition, by adding items such as the unrealized profit / loss ratio and holding period to the unrealized profit / loss level trading data as appropriate, or by aggregating by issue or period, unrealized profit / loss level trading data suitable for the purpose is created.

(Effect of unrealized profit / loss level trading data)
An example will be described in which the trading data subject to aggregation by period is aggregated for each component issue. In the case of each period, the calculation of the old method is a complicated calculation, but by processing the trading data, it is possible to more easily create unrealized profit / loss trading data for each period, and evaluate the period. It has the effect of facilitating and processing unrealized profit / loss level trading data by totaling by brand or by purchase date.

(Effect of combining unrealized gain / loss level trading data and trading data by component) 2021/02/25 addition (Definition of trading data by component of unrealized gain / loss level trading data)
Unrealized profit / loss level By classifying (aggregating) trading data by component trading data, various things can be done. There are as many different things as there are components, but here are some specific examples.

(Technical index value edition)
What will be possible if the information processing system creates unrealized profit / loss level trading data with the components as technical index values in the trading data to be aggregated by investor? Investor A's unrealized gain / loss level trading data is divided into RSI of less than 20%, 20% or more and less than 50%, 50% or more and less than 80%, and 80% or more, with the technical index value as RSI, and trading according to the classification criteria. Divide the data. Then, the stocks held by the investor are classified according to the range of RSI. At this time, the RSI at the time of purchase (RSI associated with the purchase) may be used, or the current price RSI (RSI associated with the current price) may be used. So far, we have created trading data for each component. Even with this alone, the screen of the investor A holding stock list is displayed in the classification according to the current RSI range.

(Corporate performance)
Investor A's unrealized profit / loss level trading data is used as a component of the latest corporate performance of the stocks held, and the upward revision for the last 3 months is 20% or more, less than that, no revision, downward revision 20% or less, downward revision 20%. Divide by the above, and divide the trading data according to the classification criteria. Then, the stocks held by investors are classified according to the degree of recent revision of business performance.

(Conventional issue)
In order to manage the status of the stocks held, it is important that various information is gathered there, and it is ideal that the necessary information is lined up like a dashboard, not scattered. be. This varies depending on the user, and performance-oriented users need performance-related information, and technical-oriented users hold technical-related information if it is displayed in the holding list. It will help you decide what to do with the stock. The above example is only a part that can be utilized when using the trading data by component.

(Action of trading data by component of unrealized profit / loss level trading data)
First, create unrealized profit / loss level trading data. After that, the extraction condition investor = investor A is used as the trading data to be aggregated by investor. Of course, the opposite is also possible. Then, if the aggregation target trading data for each component is set to the classification standard: RSI, it is classified by RSI. If an RSI classification table is prepared and connected by relationships, it will be aggregated or classified according to the above classification criteria.

(Effect of trading data by component of unrealized profit / loss level trading data When trading data by component is used in this way, information necessary for investor judgment can be displayed on one screen. Structure of trading data Although it needs to be an element, information associated with the issue (corporate performance, various events, themes), information associated with the date and issue (technical index values, etc.), evaluation indicators, etc. can all be captured by this mechanism. It will be possible to create a dashboard and centrally manage the necessary information of the stocks held. It is the combination of this component-specific trading data and unrealized profit / loss level trading data that has various possibilities.

(Specific example of trading data by component of unrealized profit / loss level trading data)
There are many more concrete examples. Stock market themes are topics that individual investors like. It is also possible to list stocks with the same theme as the stocks held and display a ranking of which stocks have risen the most during this holding period. All of this information can be provided because the information processing system can acquire the information in a consistent flow from the second step. It is possible to go one step further and derive the probability of subsequent success on this subject.

(What is unrealized profit / loss level trading data)
The third level separates the unrealized gain data and the unrealized loss data, while the second level adds up the unrealized gain data and the unrealized loss data, so the evaluation index of the entire unrealized profit and loss is calculated and aggregated. Evaluate the overall picture of the holding status of.

(Significance of linked unrealized profit / loss level trading data)
Unrealized gain / loss level trading data deals with trading data that does not carry out counter-trading, but goes one step further and introduces the concept of unrealized gain / loss formation funds that are the basis of unrealized gain / loss level trading data in the case of linked evaluation. By doing so, it becomes a model that includes the compound interest effect, the principle of leverage, and the cash ratio (any one is fine).

(Definition of unrealized profit and loss formation funds)
Unrealized gain / loss formation funds, as the name implies, are the funds that are the basis for forming unrealized gains / losses.

Expressing how much the current total valuation amount has increased from the principal, total valuation amount = principal + total profit. On the other hand, if the total valuation amount is reconsidered as the current balance, it will be unrealized profit / loss formation fund + cash + unrealized profit / loss. To explain from the simplest example, if you invest 100% of Mr. S's principal (1 million yen) and the price of the brand rises by 10%, 1 million yen + 100,000 yen = 1.1 million yen is the general comment. It is a value, and the relationship that the total profit amount is 100,000 yen and the principal is 1 million yen is established. On the other hand, since 100% of the unrealized profit / loss formation fund is invested, it will be 1 million yen and the unrealized profit / loss will be 100,000 yen.

Next, assuming that the stocks owned by Mr. S continued to rise and tripled, looking at the case where profits were confirmed here, the valuation amount was 1 million yen + 2 million yen = 3 million yen, and the total The profit amount is 2 million yen and the principal is 1 million yen. (See Fig. 109) On the other hand, the unrealized profit / loss formation fund is 0 because it was sold, the cash is 3 million yen, and the unrealized profit / loss is not held.

Next, Mr. S spends 100% of this 3 million yen to purchase brand A, and if brand A rises by 10%, the total valuation is 3 million yen + 300,000 yen = 3.3 million yen, and the gross profit. The relationship is that the amount is 2.3 million yen and the principal is 1 million yen. On the other hand, since the unrealized profit / loss formation fund is 100% invested, it will be 3 million yen and the unrealized profit / loss will be 300,000 yen (see FIGS. 109 and 88).

On the other hand, even if you start with the same 1 million yen, Mr. A who has not made a profit yet, even if you purchase the same A brand in full at the same time, the total evaluation amount is 1 million yen + 100,000 yen = 1.1 million yen, and the total profit amount Is 100,000 yen and the principal is 1 million yen. On the other hand, since 100% of the unrealized profit / loss formation fund is invested, it will be 1 million yen and the unrealized profit / loss will be 100,000 yen. Even if you start with 1 million yen principal at the same time and invest the entire principal of A brand at the same time, Mr. S has an unrealized profit and loss of 300,000 yen with an unrealized profit and loss formation fund of 3 million yen, while Mr. A Is an unrealized gain / loss formation fund of 1 million yen and is only an unrealized gain / loss of 100,000 yen (see Fig. 109). Mr. S has a compound interest effect, so even with the same 10% increase, it will increase by 300,000 yen, which is a 30% increase when considering the principal. On the other hand, Mr. A still has an increase of only 10% from the principal, because the compound interest effect is not working. Here, the concept of unrealized profit and loss formation funds comes into play. The snowball increase is due to the increase in this unrealized profit and loss formation fund. Speaking of the comparison between Mr. A and Mr. S, there was a difference of 1 million yen and 3 million yen before I knew it, so the latter is becoming more and more superior.

FIG. 47 is a diagram showing a specific example of a compound interest effect diagram, leverage, and no leverage according to the present embodiment.

Principal + trading profit / loss-cash = unrealized profit / loss formation fund or (principal + trading profit / loss-cash) x leverage rate (purchase price / credit collateral, generally 3.3 times for securities companies, up to 25 times for FX, virtual currency (Doubled and fluctuates depending on the time) = Unrealized gain / loss formation fund The former is the case of cash transactions that are not leveraged.

The latter is the case of leveraged margin trading.

For example, if the principal is started at 500,000 yen and the initial trading profit is 1 million yen, in the case of physical trading, 1 million yen will be left as cash out of the 1.5 million yen. In the case, if the unrealized profit / loss formation fund doubles at 500,000 yen, the unrealized gain will be 500,000 yen and the valuation amount will be 2 million yen (see the figure without leverage in Fig. 47).

On the other hand, when leveraged, even if the trading profit of 1 million yen is the same, the collateral fund will be 1.5 million yen, and even if 1 million yen of cash is left in the same way, the open interest will be 1.5 million yen. A total of 5 million yen, which is 3 times the yen, 4.5 million yen, and 500,000 yen in cash will be the unrealized profit and loss formation fund, and if it is doubled, it will be 11 million yen (cash 1 million yen, unrealized gain 5 million yen). , Unrealized profit / loss formation fund (5 million yen) is the valuation amount (see the leveraged figure in Fig. 47).

The unrealized profit / loss formation fund increases as the profit is fixed, and increases as the leverage increases. The more you spend all your investment without leaving cash, the more unrealized profit and loss formation funds will increase. Therefore, the unrealized profit / loss formation fund is affected by the principal, trading profit / loss, leverage ratio, cash ratio, and the like.

In the case of linked unrealized profit / loss level trading data, by incorporating such a concept, compound interest effect, leverage effect, and cash ratio are incorporated, and it is possible to make an evaluation that is dramatically improved compared to the old method.

(Issues of linked unrealized profit / loss level trading data)
Unrealized profit / loss level trading data can be used to create unrealized profit / loss level trading data by extracting and processing trading data, and it has become possible to evaluate unrealized profit / loss based on this. However, unrealized gains / losses are greatly affected by trading gains / losses, cash ratios, leverage effects, and the like. The old method was different from the past trading results, but the linked unrealized profit / loss level trading data is linked to the past trading, leverage effect, etc., so it is possible to make a more realistic evaluation. It has a significant effect.

(Means of linked unrealized profit / loss level trading data)
As explained in the definition of unrealized gain / loss formation fund, unrealized gain / loss formation fund + cash + unrealized gain / loss = total valuation amount = principal + total profit (trading gain / loss + unrealized gain / loss), and unrealized gain / loss formation fund = principal + Profit and Loss-Cash. Therefore, in the case of linked unrealized profit / loss formation funds, it is important to add principal, trading profit / loss, and cash to the unrealized profit / loss table. These numbers are incorporated into the unrealized profit / loss model by entering a fixed value (the value at that time) for each trading data or by entering these amounts in the total value column. Furthermore, by adding the unrealized profit / loss formation fund / principal = compound interest effect to the item, it becomes one of the important evaluation indexes. In the specific example of Mr. A and Mr. S, the compound interest effect index of Mr. A is 1 million yen / 1 million yen, and the compound interest effect index of Mr. S is 3 million yen / 1 million yen, which is 3 (Fig.). (See 109 and Figure 88), the compound interest effect is properly incorporated into the table, which allows it to be added to the evaluation index as well as the evaluation of the holding status, and it is a trading data that is fully effective in steps such as comparison. Will be. The trading data created in this way is defined as linked unrealized profit / loss level trading data.

The information generation unit 3021 processes the unrealized profit / loss level trading data to create linked unrealized profit / loss level trading data (it may be held in the previous process).

Unrealized profit / loss level Since the total purchase amount of trading data is "principal + trading profit / loss-cash", if three items are added and leverage is effective, the leverage rate and open interest are added. By adding the total purchase price of the actual product, the linked unrealized profit / loss level trading data is created by the information processing system (it may be held in the previous process).

During the unrealized gain / loss, the unrealized gain / loss formation fund does not increase, but when the unrealized gain / loss is realized, the cash increases / decreases and the trading gain / loss also increases / decreases. Therefore, when the unrealized profit / loss is realized, the trading profit / loss increases / decreases, and the linked type in which the cash increases / decreases becomes the linked type unrealized profit / loss level trading data.

By this mechanism, the past trading profit / loss forms the current unrealized profit / loss, and the current unrealized profit / loss becomes the trading data incorporating the relationship that produces the future trading profit / loss (see the compound interest effect diagram in FIG. 47).

In the case of leverage, the open interest, the leverage ratio, and the unrealized profit / loss formation fund in kind are added, and the sum of the open interest and the unrealized profit / loss formation fund in kind is the unrealized profit / loss formation fund.

(Effect of linked unrealized profit / loss level trading data)
By creating linked unrealized profit / loss level trading data, cash ratio, trading profit / loss ratio, unrealized profit / loss ratio, cash opportunity loss, etc. can be easily calculated, which has the effect of raising the evaluation level of unrealized profit / loss level trading data. be.

Cash ratio = cash / (trading profit / loss + unrealized profit / loss + principal)
Trading profit / loss ratio = trading profit / loss / (trading profit / loss + unrealized profit / loss + principal)
Unrealized gain / loss ratio = Unrealized gain / loss / (Trading gain / loss + Unrealized gain / loss + Principal)
Compound interest effect index = Unrealized profit / loss formation fund / principal.

(Effect of linked unrealized profit / loss level trading data)
Normal unrealized gains / losses level Trading data does not include trading gains / losses in the model and is out of control. However, if the model of linked unrealized profit / loss level trading data is used, a special effect can be expected in which trading profit / loss, cash, compound interest effect index, and principal are incorporated into the model, and the current situation can be accurately grasped. In the previous trading table of Mr. S, the items of 1 million yen of principal, 2 million yen of trading profit and loss, and compound interest effect index of 3 are added, so the valuation index that can be managed increases, and even in the valuation step, the current The effect that these evaluation indexes can be used for the evaluation of the situation can be expected to be immeasurable. The difference is clear even if you grasp the current situation of Mr. A and Mr. S. In the evaluation index calculated from the normal unrealized profit / loss level trading data, the current situation is that Mr. A, who has an investment of 1 million yen and has become 1.1 million yen, with a 10% increase in the stock A he owns. Only the difference in the investment amount from Mr. S, who is 3.3 million yen with an investment of 3 million yen, which is a 10% increase in the A brand, is at the grasp level. On the other hand, in the case of linked unrealized profit / loss level trading data, Mr. A, who has a 10% increase in the holdings of A stock and has an investment of 1 million yen to 1.1 million yen, has a principal of 1 million yen, which is still It can be understood that there is no compound interest effect and trading honor has not been achieved, while Mr. S, who has invested 3 million yen to 3.3 million yen with a 10% increase in the A stock he owns, is also the same. If you start with a principal of 1 million yen, have already recorded a past profit of 2 million yen, and the compound interest effect index has reached 3, there is an effect that you can make the difference clear. The current situation originally comes from the past accumulation, but while the normal unrealized gain / loss level trading data does not grasp this past accumulation, the linked unrealized gain / loss level trading data is the past accumulation. It is an invention that incorporates the fact that the result of the above is the current state, which will bring a great effect to the subsequent process. This is an epoch-making invention for grasping the current status of investment because the portfolio for grasping the current status does not have this concept and is managed by the normal unrealized profit / loss level trading data.

Furthermore, in the case of margin trading, (principal + trading profit / loss-cash) x leverage ratio will be added to the model. By adding the leverage rate to one of the items, the compound interest effect index will further increase. For example, if the leverage rate is 1x, the compound interest effect index is 3 in the previous example of Mr. S, but assuming that Mr. Z doubles the leverage, the unrealized profit and loss formation fund is doubled to 6 million. It becomes a circle. 10% of 6 million yen is 600,000 yen. Mr. A will be 100,000 yen, Mr. S will be 300,000 yen, and Mr. Z will be 600,000 yen. This is the result of doubling the leverage rate and doubling the compound interest effect index (see FIGS. 109 and 88). By adding this leverage effect to the items, the effect of clarifying the principle of leverage and the actual condition of the compound interest effect is immeasurable.

By adding the open interest of credit to the valuation, it becomes possible to understand the situation of how much unrealized gain and unrealized loss are currently held in margin trading. Generally, there are announcements such as the valuation loss rate and the quantity of open interest, but the actual state of open interest in credit is wrapped in a veil, and the merit of this information is very large. Open interest information is information that even securities companies are sensitive to, and I think it is difficult to get out to the world, but just because there is open interest information, this linked unrealized profit / loss level trading data can dramatically grasp the actual situation of investors. Useful for.

(Specific example of linked unrealized profit / loss level trading data)
By incorporating the concept of unrealized profit and loss formation funds, past trading and current trading will be connected, and the actual situation of trading in which profits call for profits will be well understood. This leveling effect, which is one of the causes of investment disparity, and the compound interest effect, which increases like a snowball, are difficult to understand even with ordinary portfolio information, and are also one of the causes of investment disparity. The significance of creating linked-type unrealized profit / loss level trading data is great.

(Specific example of linked unrealized profit / loss level trading data)
This point is also detailed in the evaluation step.

(What is unrealized profit / loss level trading data)
While the 3rd level separates the unrealized gain data and the unrealized loss data, the 2nd level combines the unrealized gain data and the unrealized loss data, so the evaluation index of the entire unrealized profit and loss is calculated and the holdings to be aggregated. Evaluate the big picture of the condition.

(Old method of 3rd level trading data)
The first embodiment describes a method of calculating an evaluation index of a winning rate of return, an evaluation of a winning profit, a calculation of an evaluation index, a decomposition formula, and an evaluation of a winning profit rate (unrealized profit rate). However, the types of evaluation indicators, diagnostic procedures, decomposition formulas, etc. are described.

(Definition of 3rd level trading data)
The trading data at the trading profit / loss level and the trading data at the unrealized profit / loss level are not separated into wins and losses, and are trading data for grasping the whole trading and holding status (FIGS. 45 and 45). See 46).

On the other hand, the third level trading data is trading data that separates the trading data that generated the winning profit and the trading that caused the losing loss, and is the case of the fixed profit data (winning profit trading data) and the undetermined profit. There is a profit in the case of (unrealized gain trading data). The same applies to the loss.

(Issues of 3rd level trading data)
In the old method, for example, there is a method of grasping the winning profit by a decomposition method, but especially for the way of understanding by dividing the period and for viewing the trading data in detail for each trading data, this third level trading data Is more suitable.

(Action of 3rd level trading data)
The information generation unit 3021 is based on the aggregated trading data, the trading data satisfying "buy price (or market price at time A) <selling price (or market price at time B or current price)" from the second level trading data, and " Bid price (or market price at time A) ≥ selling price (or market price at time B or current price) ”is extracted and processed to create third-level trading data.

The information generation unit 3021 revalues the trading data subject to aggregation by period from the purchase market price to the A time point market price in the case of the investment product held at point A, and evaluates from the sale market price to the B time point market price in the case of the investment product held at point B. By substituting, the third level trading data is created.

Specifically, the information generation unit 3021 revalues the unit price of the product whose purchase date is before the time A at the market price at the time A, and revalues the unit price of the product whose sale date is after the time B at the market price at the time B. Create third level trading data. In addition, the information generation unit 3021 adds items such as a winning profit margin, aggregates components such as aggregation for each product, processes them into third-level trading data suitable for the purpose, and creates the data.

(Effect of 3rd level trading data)
For example, when evaluating a sale that wins and earns a profit in 2019, investment products purchased at a low market price in 2012 are highly evaluated based on the purchase unit price. If you want to divide the valuation by period, this is inconvenient, so by revaluing at the market price at point A (early 2019), you will be able to accurately grasp the results of 2019, and the winning profit of 2019 will be There is an effect that the evaluation can be performed accurately. Furthermore, by adding items such as the winning profit rate to the third level trading data as appropriate, it is possible to evaluate each trading data, and by aggregating each component, the winning profit is constructed. It also has the special effect of being able to evaluate each component.

(What are winning profit level trading data and losing loss level trading data)
The winning profit level trading data is the winning profit (fixed profit) level trading data obtained by extracting the trading profit / loss level trading data under the condition of "buying price <selling price or market price at time A <selling price (realized profit level)", or "buying price <". It refers to the winning profit (undetermined profit) level trading data extracted under the condition of B time point market price (or current price) or A time point market price <B time point market price (or current price) (unrealized profit level) ".

The losing loss level trading data is the opposite (replace <with ≧ in the description of the winning profit level trading data).

The 4th level classifies the profit-taking level trading data into 3 categories according to the hierarchical relationship between the buying price, the selling price, and the market price after the sale, while in the winning profit level, all the data satisfying "buying price <selling price" are integrated. There is. At the winning profit level, it doesn't matter whether the profit-determined data drops significantly or rises after the sale. On the other hand, at the 4th level, an evaluation of what happened after the sale is added. An evaluation index for the entire fixed profit is calculated and evaluated.

(Issues of winning profit level trading data)
In the old method, for example, there is a method of capturing the winning profit in a decomposed manner, but the creation of the winning profit level trading data is more suitable for grasping by period or for examining the trading data in detail. ..

For example, as shown in FIGS. 38 and 40, the winning profit level trading data is extracted and arranged in descending order of the contribution of the winning profit, or the trading period, the trading profit / loss, and the purchase amount are arranged by the annualized rate of return. It is possible to show the profit composition ratio for each stock and show the stocks with a high degree of profit contribution. As is clear when comparing FIGS. 38, 39 and 40, FIG. 39 is suitable for grasping the whole picture, while FIGS. 38 and 40 evaluate detailed data for each issue and investor. Has the effect of being possible.

The difference between this old method and the new method is not only the winning profit level trading data, but also the losing loss level trading data, the unrealized profit / loss level trading data, the trading profit / loss level trading data, the total profit / loss level trading data, and the fourth level trading data. The same is true. At all levels 1 to 4, the difference between the old method and the new method is clear.

(Means of winning profit level trading data)
The information generation unit 3021 extracts and processes only the trading data satisfying the "buying price (or the market price at the time of A) <selling price" from the trading profit / loss level trading data based on the trading data to be aggregated, and processes the winning profit level trading. Create the data.

The information generation unit 3021 extracts the trading data whose purchase date or sale date is within the AB period from the aggregated trading data for the period-specific aggregation target trading data, and the purchase date is before the A time point and is in the AB period. Extract the trading data of the sale or the purchase after the time A and the sale before the time B. The trading data of the sale on the purchase date before the time A and during the AB period is revalued to the market price at the time A.

The information generation unit 3021 further adds items such as a winning profit rate and a trading period to the trading data, and creates the data by performing totaling for each issue, period totaling, profit rate range totaling, and the like. The information generation unit 3021 creates winning profit level trading data by revaluing the investment products held at the time A from the market price at the time of purchase to the market price at the time A. Specifically, the information generation unit 3021 creates winning profit level trading data by revaluing the unit price of the trading products held before the purchase date at the time A at the market price at the time A.

(Effect of winning profit level trading data)
For example, when evaluating a sale that wins and earns a profit in 2019, investment products purchased at a low market price in 2012 are highly evaluated based on the purchase unit price. If you want to divide the valuation by period, this is inconvenient, so by revaluing at the market price at point A (early 2019), you will be able to accurately grasp the results of 2019, and the winning profit of 2019 will be There is an effect that the evaluation can be performed accurately. Furthermore, by adding items such as the winning profit rate to the winning profit level trading data as appropriate, it is possible to evaluate each trading data, and by aggregating each component, the winning profit is composed. It also has the special effect of being able to evaluate each component.

(Old method of unrealized profit / loss level trading data)
In the first embodiment, there is a description of a method of calculating an evaluation index of a winning profit rate (unrealized profit rate).

(Definition of unrealized profit / loss level trading data)
The unrealized profit / loss level trading data is not divided into winning and losing, and is trading data for grasping the whole picture of the holding situation. The third-level trading data is trading data in which the trading data that generated the winning profit and the trading data that caused the losing loss are separated. The trading data that aggregates the profits in the case of undetermined (unrealized profit / loss trading data) is the winning profit (unrealized profit or unrealized profit) level trading data. The trading data that aggregates the losses in the case of undetermined (unrealized profit / loss trading data) is the losing loss (unrealized loss or unrealized loss) level trading data.

(Issues of unrealized gain level trading data)
In the old method, for example, the calculation of the unrealized rate of return is shown in the first embodiment, but the winning profit (unrealized profit) is divided into periods, the trading data is examined in detail, and the aggregation for each component is performed. This unrealized profit level trading data is more suitable for the effect of going and so on.

(Action of unrealized gain level trading data)
The information generation unit 3021 extracts and processes only the trading data satisfying "buying price <market price at time B (or current price)" from unconfirmed trading data that has not yet been counter-traded based on the aggregated trading data. Then, the unrealized profit / loss level trading data is created (it may be held in the previous process).

The information generation unit 3021 creates unrealized profit / loss level trading data by revaluing the above trading data from the purchase market price of the investment product held at time A to the market price at time A (previous step). You can bring it to).

Specifically, the information generation unit 3021 creates unrealized profit / loss level trading data by revaluing the unit price of the products held before the purchase date A at the market price at the time A among the held products (in the previous process). You can have it). Furthermore, items such as holding period and unrealized profit rate are added, and processing such as issue aggregation, period aggregation, and rate of return range aggregation is performed to create unrealized profit / loss range trading data.

(Effect of unrealized gain level trading data)
For example, when evaluating owned products that gained unrealized gains in 2019, investment products purchased at a low market price in 2012 will be highly evaluated based on the purchase unit price. If you want to divide the valuation by period, this is inconvenient, so by revaluing at the market price at point A (early 2019), you will be able to accurately grasp the results of 2019, and the unrealized gain from holding in 2019. It has the effect of being able to accurately evaluate. This is one of the effects of creating trading data subject to aggregation by period, and the actual situation of the stocks held can be understood. Even with the same unrealized gain evaluation, such as the unrealized gain increase rate in 2019 and the unrealized gain increase rate in 2020, it is possible to make a deep evaluation and it is very effective in grasping the actual situation.

(What is winning profit (unrealized profit or unrealized profit) level trading data, losing loss (unrealized loss or unrealized loss) level trading data)?
The winning profit (unrealized profit or unrealized profit) level data is the winning profit (unrealized profit level) obtained by extracting the unrealized profit / loss trading data under the condition of "buy price <market price at time B or market price at time A <market price at time B (unrealized profit level)". Profit) level trading data. The losing loss level is the opposite of the winning profit level (replace <with ≧).

The 4th level trading data is classified into two categories according to the hierarchical relationship of the bid price (or the market price at the time of A), the market price at the B time, the buy price (or the market price at the time of A) x the market price of the benchmark rate of increase / decrease, but the winning profit (unrealized). In the profit) level trading data, all the data satisfying "Bid price (or market price at time A) <current price (or market price at time B)" are integrated.

At the third level, the data containing profits, good or bad compared to the benchmark, does not matter. On the other hand, at the 4th level, an evaluation of how it compares with this benchmark is added. An evaluation index for the total unrealized profit is calculated and evaluated.

(What is winning profit (unrealized profit or unrealized profit) level trading data)
The third level separates the winning profit (unrealized profit or unrealized gain) level trading data and the losing loss (unrealized loss or unrealized loss) level trading data, while the fourth level has the same unrealized gain data. An index of whether or not it exceeds the benchmark is added. At this level, an evaluation index for the entire unrealized gain is calculated and evaluated regardless of whether or not it exceeds the benchmark.

(Old method of linked unrealized profit / loss level trading data)
Compared to the above-mentioned unrealized profit / loss level trading data, the following items are added to the trading data for processing. To the total value, add one or more cash and unrealized gain / loss total, principal, trading profit / loss, and in the case of leverage, leverage ratio, unrealized gain formation open interest, unrealized loss formation open interest, unrealized gain formation fund in kind, and unrealized loss formation fund in kind. ..

(Definition of unrealized profit / loss level trading data)
Unrealized gain / loss level The above-mentioned unrealized gain / loss level trading data is added with items such as trading gain / loss, cash, and principal, and the unrealized gain / loss formation fund is the result of past trading, and the current unrealized gain / loss plays a role in forming future trading gain / loss. It is the linked unrealized profit / loss level trading data that adds an item that connects the past, present, and future.

(Issues of linked unrealized profit / loss level trading data)
The unrealized profit / loss level trading data does not take into account the results of past trading and the situation in which cash is placed without contributing to the unrealized gain, and the evaluation is different from other situations. However, in reality, past trading profits and losses have a great influence on the current unrealized profits and losses, and it is necessary to evaluate them, including the funds for unrealized profits and losses.

(Action of linked unrealized profit / loss level trading data)
Unrealized profit / loss level Create by adding the following items to the trading data. That is, a linked item is added to the total amount line.

(Definition of interlocking items)
A linked item is an item that links unrealized gains and losses with trading gains and losses. The trading profit / loss is the result of past trading, and the unrealized profit / loss represents the profit / loss currently in progress. Unrealized gains / losses are linked to past results and are linked to future trading gains / losses. Items that play a role in connecting past results and future trading profits and losses are defined as linked items. Linked items include cash, cash ratio, unrealized loss formation fund, unrealized gain formation fund, trading profit and loss, principal, leverage ratio, open interest, unrealized gain formation open interest, and unrealized loss formation open interest.

As the trading profit increases, the unrealized profit / loss formation fund increases, and as a result, the unrealized profit / loss also increases or decreases. As the cash ratio rises, the unrealized profit / loss formation fund decreases and the unrealized profit / loss increases / decreases. If the leverage ratio increases or the open interest increases, the unrealized gain or loss will increase. Therefore, these are also interlocking items. Items having such a relationship are defined as interlocking items.

(Effect of linked unrealized profit / loss level trading data)
Unrealized profit / loss level By adding linked items to trading data, it is possible to measure effects such as compound interest effect and leverage effect by connecting past trading with current unrealized profit / loss formation and future trading profit / loss. It can also be expected to be effective in raising ranks such as diagnosis, comparison, and ranking.

(Specific example of linked unrealized profit / loss level trading data)
FIG. 60 is a diagram showing a specific example of linked unrealized profit / loss level trading data according to the present embodiment. As shown in the lower part of FIG. 60, for example, there is a breakdown of what kind of trading the trading profit / loss of 16.25 million yen has been carried out in a linked manner, such as 175 trading times and 92911 yen per trading profit / loss. It is linked. For example, if the trading profit / loss per transaction rises from 92911 yen to 100,000 yen and the number of trading times rises to 180 times, the trading profit / loss will be 18 million yen, and the total of cash and unrealized profit / loss formation funds will also be from 16.25 million yen. The relationship will increase to 18 million yen.

(What is winning profit (unrealized profit or unrealized profit) level trading data and losing loss (unrealized loss or unrealized loss) level trading data)?
The winning profit (unrealized profit or unrealized profit) level is the winning profit (unrealized profit) obtained by extracting the unrealized profit / loss trading data under the condition of "buy price <market price at time B or market price at time A <market price at time B (unrealized profit level)". ) Level trading data. The losing loss level is the opposite of the winning profit level (replace <with ≧).

(Old method of 4th level trading data creation process)
In the first embodiment, there is a description of a basic numerical value, an evaluation index, and a decomposition formula for a winning pattern, and a description of a pattern classification of owned products.

(Significance of creating 4th level trading data)
At the 4th level, an evaluation of what happened after the sale or how it was compared to the benchmark is added.

The information generation unit 3021 further adds the market price after sale to the winning profit level trading data and the losing loss level trading data as trading data items (including the table method of FIG. 86), and the hierarchical relationship between the buying price, the selling price, and the market price after selling. Create the winning pattern level trading data and the losing pattern level trading data classified in.

The information generation unit 3021 further adds a benchmark-compatible market price (including the table method of FIG. 86) as a trading data item to the unrealized gain level trading data and the unrealized loss level trading data, and the buy price (or the market price at the time A) and the current price (or the market price B). The unrealized gain pattern level trading data and the unrealized loss pattern level trading data are created by dividing the pattern according to the positional relationship of market price) and benchmark rate of increase / decrease x buying price (or market price at time A).

(Issues of 4th level trading data)
At the third level, only the overall picture of fixed profit and loss, unrealized gain and unrealized loss data is known. From there, by creating trading data that further classifies the patterns, more detailed information such as winning patterns of buying and selling and winning patterns of owned products can be obtained.

Moreover, in the old method, the calculation of the evaluation index is more important than the creation of the fourth level trading data. By clarifying the process of creating the 4th level trading data, it becomes easier to compare the situation of each individual stock with others, and it becomes possible to make a wider evaluation that is more applicable.

In particular, at the 4th level stage, the data becomes finer and tends to be difficult to understand with a list of numbers. For example, simply displaying the trading data of the winning pattern 1 in a list has the effect of obtaining various information such as clarifying which brand is winning and how. It is particularly effective for trading data subject to aggregation by period.

(Means of 4th level trading data)
The information generation unit 3021 extracts only the trading data that has already been confirmed by counter-trading from the trading data to be aggregated, and further, "buying price (or the market price at the time A) <the selling price or the buying price (or the market price at the time A)). ≧ Sell price ”is extracted, and the market price after sale is added to the trading data items, and it is classified into 3 patterns according to the positional relationship of the buy price (or the market price at time A), the sell price, and the market price after sale, and each pattern wins. (Or lose) Create pattern level trading data.

The information generation unit 3021 extracts only unconfirmed trading data that has not yet been counter-traded from the aggregated trading data, and further, "buy price <current price (or market price at time B) or buy price ≥ current value". (Or the market price at the time of B) ”is extracted, and the market price corresponding to the benchmark is added to the trading data items (including the table method in FIG. 86), and classified into two patterns according to the positional relationship between the benchmark market price and the selling price. , Unrealized gain (or unrealized loss) pattern level Create trading data.

(Effect of 4th level trading data)
By evaluating each of the three patterns of winning profit (losing loss) data in the traded data, which pattern is the fixed profit (loss) to be aggregated, what is it, and the average holding You can get information on the winning pattern, such as what the period is and what the profit rate (loss rate) is.

By evaluating each of the two patterns of unrealized gain (unrealized loss) data in the undetermined data, what pattern is the unrealized gain (unrealized loss) to be aggregated, what is it, and what is the average holding period? Yes, you can get detailed information on the unrealized gain, such as what the unrealized gain ratio (unrealized loss ratio) is.

In addition, by creating the winning pattern trading data, which was not revealed in the old method, there is an effect that it is possible to individually know in detail what kind of trading the winning pattern is.

For example, if the stock A is confirmed, an index of what happened after the sale is added, and if it is undetermined, an index of whether it is better or worse than the benchmark is added, so that a deeper analysis becomes possible.

(Old method of winning pattern level trading data creation process)
In the first embodiment, the winning pattern is described in the decomposition formula of the winning profit, and a specific example regarding the evaluation is shown. That is, the basic numerical value, the evaluation index, and the decomposition formula of the profit of the winning pattern are described.

(Issues of winning pattern level trading data)
The old method focuses on the element decomposition formula of the winning pattern, the evaluation index, the basic numerical value, etc., and does not touch on the process of creating the winning pattern level trading data. Solve the challenges of the process of creating winning pattern level trading data. With the winning profits obtained by investing for each aggregation target, only the overall picture of the winning profit trading data can be known.

FIG. 61 is a diagram showing a specific example of trading data of the winning pattern 1 level according to the present embodiment. In the present embodiment, there are three patterns of profitable winning profit trading data depending on the price movement after sale, and trading data for each pattern is created.

(Means for creating winning pattern level trading data)
The information generation unit 3021 extracts the trading data that has already been confirmed by counter-trading from the trading data to be aggregated, extracts the data that satisfies the "buying price (or market price at time A) <selling price", and further sells. In addition to the trading data items (including the table method), the later market price is extracted in 3 patterns according to the hierarchical relationship of the buy price (or the market price at time A), the sell price, and the market price after sale, and the processed trading data wins. Create as pattern level trading data.

FIG. 62 is a diagram showing an example of a winning pattern according to the present embodiment.

(Effect of winning pattern level trading data)
By extracting (or classifying, aggregating, and processing) the trading data of each of the three patterns of winning profit trading data from the trading data, which pattern the winning profit to be aggregated is generated from, and to what extent, the average. You can get information such as how long the holding period of the stock is and what it is like to divide it into a certain period, and you can grasp the more detailed winning pattern than the old method, such as which stock has a high profit contribution. By adding the winning profit rate, trading period, etc. to the trading data items and adding the brand, period, etc. to the aggregated data, it is possible to create winning pattern level trading data according to the purpose.

(Significance of winning pattern level trading data)
By going through the process of creating winning pattern level trading data, adding winning pattern trading data to the decomposition formulas, evaluation indexes, etc. of the old method will be very effective in diagnostic ability and advice. Allows for deeper analysis.

(Definition of market price for benchmarks)
The benchmark-compatible market price is calculated by "benchmark rise / fall rate x (buy price or market price at time A) (including the table method of FIG. 86)". The benchmark rate of increase / decrease represents the rate of increase / decrease based on the benchmark value at the time of purchase or A.

(Definition of market price at time A)
The time point that becomes the starting point for each period is defined as the time A, the market price at the time A is defined as the market price at the time A, and the valuation amount at the time A is defined as the valuation amount at the time A (in the table method of FIG. 86, the stock price is always stock price). And the trading data are linked and stored in the DB of the storage unit 33, so the market price at point A includes a method that can be linked by date).

(Definition of B market price)
The time point that becomes the end point in each period is defined as the time B, the market price at the time B is defined as the market price at the time B, and the valuation amount at the time B is defined as the valuation amount at the time B (in the table method of FIG. 86, the stock price is always stock price). And the trading data are linked and stored in the DB of the storage unit 33, so the market price at point B includes the method that can be linked by date).

(Old method of creating unrealized profit / loss pattern level trading data)
In the first embodiment, there is a description that the purchase price, the product evaluation price, and the benchmark evaluation price are calculated to perform a comprehensive evaluation of the owned product. Next, there is a description of the rate of increase / decrease of commodities and the rate of increase / decrease of benchmarks. In addition, there is a description about the pattern of owned products. Furthermore, there is a description of the process of calculating the ratio of the purchase price and the product evaluation price for each pattern.

(Issues for creating unrealized profit / loss pattern level trading data)
With unrealized gains and losses, only the overall picture of unrealized gains and losses level trading data is known. There are two patterns of unrealized profits that are profitable, depending on whether they are higher or lower than the market value for benchmarking. Further, in the old method, there is a description about the ratio for each pattern, but there is no description or suggestion in the creation method for extracting and processing the trading data. Unrealized profit / loss pattern level The problem is solved by the process of creating trading data.

(Means for creating unrealized profit / loss pattern level trading data)
The information generation unit 3021 extracts unconfirmed trading data that is not counter-trading from the aggregated trading data, further extracts data that satisfies "buy price <current price (or market price at time B)", and further extracts data that satisfies "buy price <current price (or market price at time B)". In addition to the trading data item, the market price corresponding to the benchmark is classified into two patterns according to the positional relationship between the market price corresponding to the benchmark and the current price (or the market price B market price), extracted, and appropriately processed to create the unrealized profit / loss pattern level trading data. do. FIG. 59 is a diagram showing an example of unrealized profit / loss pattern level trading data according to the present embodiment.

(Effect of unrealized profit / loss pattern level trading data)
By evaluating each of the two patterns of unrealized gain data in the undetermined trading data, which pattern is the unrealized gain to be aggregated, how much is it, what is the average holding period, and how can it be compared with the benchmark? You can see detailed information on the unrealized gain, whether it is bad or not.

Furthermore, in the old method, there is a description that the total purchase price or the product evaluation price is calculated for each of the four patterns, the ratio of the price of each pattern to the total of the four patterns is calculated, and the ratio of each pattern is calculated. , Unrealized profit / loss pattern level There is no description regarding the creation of trading data. By creating trading data at the unrealized profit / loss pattern level, the details of each pattern will be clarified, and it will have a special effect on diagnostic power and advice.

By adding the winning profit rate and holding period to the trading data items, and adding the brand, purchase time, etc. to the aggregated data, it is possible to create unrealized profit / loss pattern level trading data according to the purpose.

(Significance of unrealized profit / loss pattern level trading data)
The fourth level classifies the unrealized profit / loss data into two categories according to the hierarchical relationship of the bid price, the current price, and the benchmark-compatible market price, and divides the evaluation according to whether the market price is above or below the benchmark-compatible market price. In the case of stocks, in the case of successful cases, there are many cases of "buy price <benchmark compatible market price <current price", and it can be evaluated that the stock with the correct answer is held continuously. It has the effect of making it clear at a glance the list of stocks that have exceeded these benchmarks and how much they have exceeded. Allows for deeper analysis.

(Old method of creating linked unrealized profit / loss pattern level trading data)
The information generation unit 3021 creates the linked unrealized profit / loss pattern level trading data by adding the linked item at the time of creating the above-mentioned unrealized profit / loss pattern level trading data.

(Issues for creating linked unrealized profit / loss pattern level trading data)
Unrealized profit / loss pattern level trading data is disjointed data that does not include the results of past trading and is not linked to trading profit / loss. Unrealized profit / loss pattern level By adding linked items to trading data, the unrealized profit / loss pattern and trading profit / loss are connected, and the funds increase / decrease in trading profit / loss starting from the principal, and unrealized profit / loss excluding unused cash. The formation fund increases or decreases. Among them, the unrealized profit / loss formation fund forms the unrealized profit / loss, and the fund that forms the unrealized profit exceeding the benchmark is generated. If leverage such as margin trading is effective, the financial power will further increase, and the unrealized profit and loss formation funds will increase or decrease, and it will be important to add these evaluations as well.

(Means for creating linked unrealized profit / loss pattern level trading data)
The information generation unit 3021 creates the linked unrealized profit / loss pattern level trading data by adding the linked item to the unrealized profit / loss pattern level trading data.

(Effect of linked unrealized profit / loss pattern level trading data)
For example, the current holding status can be grasped more accurately depending on how much weight the unrealized gain pattern exceeding the benchmark occupies in the unrealized profit / loss formation fund.

For example, in the case of 80%, the current holding status can be evaluated as good because the unrealized gain-forming funds account for the majority of the investment products currently held and the unrealized gain-forming funds, which exceed the benchmark, account for 80%. However, if the cash ratio is too high, there is an opportunity loss and it is necessary to discount it.

On the contrary, if the unrealized profit / loss formation fund below the benchmark occupies 80%, there is a lot of room for improvement and the evaluation is low. In particular, if the holding period has become long, it means that the valuation loss of the investment product is in a salted state and the funds are not being utilized. The smaller the cash ratio, the greater the room for improvement.

(Significance of linked unrealized profit / loss pattern level trading data)
Unrealized profit / loss formation is a barometer of whether or not the current investment product is working well, and if the past is good or the present is bad, the present improvement is required.

On the contrary, even if the past is bad, if the present unrealized gain is abundant, these unrealized gains will be reborn as trading profits in the future, and the funds will increase to become the next unrealized gain formation funds.

Since this linkage is extremely important for achieving the results of investment products, it is meaningful to create linked unrealized profit / loss pattern level trading data. Unrealized profit / loss pattern level trading data can be created in the same way.

(Automation step of creating profit / loss level trading data)
Since it is clear from the issue whether the trading profit or loss is being sought, the unrealized profit or loss is being sought, or the total profit or loss is being sought, the profit or loss level trading data according to the request is determined.

If only the trading data obtained by buying or selling is extracted from the trading data to be aggregated or the trading data by component, the trading profit level trading data is obtained, and if only the winning trade is extracted from the trading data, the winning profit level trading data is obtained.

The most important profit / loss in each is the trading profit / loss (or the trading profit / loss ratio) in the former case, and the winning profit (or the winning profit / loss ratio) in the latter case. These indicators are the most important because they are the overall results of the trading data.

The evaluation index is the most important factor that influences the profit and loss. In other words, if those evaluation indexes increase or decrease, the above-mentioned trading profit or loss and winning profit, which are the overall results, will increase or decrease.

The next step is the step of actually calculating this evaluation index. The calculated evaluation index is important because it is used for comparison, evaluation, ranking, diagnosis, advice, etc. according to the purpose.

(Calculation of evaluation index (fifth step))
1st step ・ ・ ・ Acquisition of trading data 2nd step ・ ・ ・ Creation of trading data to be aggregated 3rd step ・ ・ ・ Creation of trading data by component (even after the 4th step)
Fourth step: Profit and loss level Trading data creation step (even after the second step)
Fifth step: Step to create profit / loss level evaluation index (this step) It is said that it is related to the target profit / loss calculated from the trading data extracted (or classified, aggregated, processed) up to the fourth step. A step to calculate, select, and display an evaluation index with properties.

(Definition of step to create profit / loss level evaluation index)
The step of creating a profit / loss level evaluation index is a step of creating an evaluation index for evaluating the trading data based on the trading data created in the step of creating the profit / loss level trading data.

(Type of evaluation index for profit / loss level trading data)
Profit and loss level The types of evaluation indexes obtained from trading data include evaluation indexes (win rate, winning profit margin, etc.) obtained from trading data (transaction data) in a narrow sense, and evaluation indexes (performance forecast values) obtained from performance data of stock companies. , Upward revision rate, etc.), Evaluation indicators obtained from technical indicators used for forecasting future price movements (RSI, etc.), Evaluation indicators obtained from trading data of other investors (Purchasing the same stock on the same purchase date, etc.) Investors' average selling price, etc.), evaluation indicators obtained from trading data of other investment targets (such as the rate of return on trading of other investment targets when purchasing other investment targets on the same purchase date), etc. Will be.

(Previous technology)
In the first embodiment, a step of acquiring a total profit / loss from trading data and calculating an evaluation index with reference to the total profit / loss is shown.

It presents an evaluation index calculation process in which basic data is acquired from trading data and the evaluation index is calculated by referring to the basic data.

This is a part of the evaluation index obtained from the trading data in the narrow sense of the above type.

(Issues in the step of creating a profit / loss level evaluation index)
In order to evaluate trading data, it is necessary to create an evaluation index, and in evaluating trading data, it is important to evaluate trading data (transaction data) in a narrow sense, but trading data in a narrow sense (trading data (transaction data)). There are several methods for creating the evaluation index of (transaction data), and the first embodiment shows a part thereof.

Trading data in the narrow sense is direct trading data, but other indicators are also important for proper evaluation of trading data.

For example, by adding trading data of other investors, trading data of other investment targets, technical indicators of the investment targets, performance data of stock companies, etc. as evaluation indexes, various evaluation indexes can be created from various aspects. Is possible.

(Action of step to create profit / loss level evaluation index)
The information generation unit 3021 creates necessary evaluation indexes in the process of the first step to the fourth step.

For example, in the case of the technical index of the stock to be invested, the technical index at the time of purchase can be obtained by storing the technical index value at the time of purchase in addition to the stock price, purchase date, and number of stocks purchased at the time of purchase of the investment target. It will be possible to utilize it. Store performance data in the same way as technical index values.

Regarding the trading data of other investors, the information generation unit 3021 calculates the evaluation index from the purchase data of other investors that match the same issue on the same date as the purchase date. Regarding the trading data of other investment targets, the information generation unit 3021 calculates an evaluation index from the purchase data of other investment targets on the same date as the purchase date.

(Effect of step to create profit / loss level evaluation index)
In order to evaluate trading data, it is necessary to create an evaluation index. In addition to trading data (transaction data) in a narrow sense, the evaluation of trading data includes performance data of stock companies to be invested, trading data of other investors, technical indicators of investment targets, trading data of other investment targets, etc. By adding the evaluation index obtained from the above to the evaluation index of the trading data, it is possible to evaluate the trading data in a more multifaceted and deep manner.

(Specific example of step to create profit / loss level evaluation index)
[Evaluation index obtained from performance data of investment target]
For example, assuming that the initial forecast of operating profit is 100, the performance data is 1 revision and 110 revisions based on the first revision of the initial forecast when purchasing with the first revision 110. It is managed by the evaluation index of. For example, the same applies to the case of the second correction value 130 (2 and 130) and the third correction value 150 (3 and 130). This is just an example, but by doing so, the evaluation index of performance data will be incorporated into the evaluation of the investment target.

[Evaluation index obtained from trading data of other investors]
The evaluation index obtained from the trading data of other investors of the investment target is also an important evaluation index in evaluating the trading data of the investment target of the investor. For example, if Investor B, who purchased stock a on the same day, continued to hold it and doubled the price range, but Investor A sold it at 1.2 times, Investor A's The valuation incorporates the concept of opportunity loss rather than simply taking a price range of 1.2 times, and it is possible to make a deeper and multifaceted valuation, such as how it is compared to other investors.

[Evaluation index obtained from the technical index of the investment target]
The evaluation index obtained from the technical index of the investment target is also an important evaluation index in evaluating the trading data of the investment target of the investor.

For example, it is possible to tell the arrival of a buying opportunity again when the a brand that buys the a brand at RSI 20% and sells it at RSI 80% and has taken a price range of 1.5 times again when the RSI falls below 20%. Will be. In addition, when the current RSI of the investment target is 10%, it is easy to calculate the rate of increase / decrease when the past RSI is 10% and then 3 months later. It increases by 15% on average, and it is possible to display something like a success probability of 80%. If these evaluation indicators can be displayed at the time of purchase, it will be very useful information for investors.

Traditionally, managing such numbers is very difficult and is not actually managed.

[Evaluation index obtained from trading data of other investment targets]
The evaluation index obtained from the trading data of other investment targets is also an important evaluation index in evaluating the trading data of the investment target of the investor.

For example, if the price range of issue a was doubled during the same trading period, but issue b stopped at 1.2 times, the valuation of issue b was not just 1.2 times, but another investment target. It is possible to make a deeper and multifaceted evaluation because the viewpoint of how to compare with is added. If you select a brand, the price range is doubled. It is possible to add various evaluation indexes such as average value and maximum price range.

(Significance of creating evaluation indicators for transaction data)
Transaction data is defined as trading data in a narrow sense in trading data. Transaction data is data related to direct trading. The information generation unit 3021 uses a series of evaluation indexes derived from transaction data such as purchase data (purchase date, purchase unit price, number of purchases) and sell data (sale date, unit price of sale, number of sales) of investment products. create.

(Problems of conventional technology)
In the first embodiment, {(win rate x purchase price of winning trade x winning profit rate / number of wins) + (loss rate x purchase price of losing trade x losing loss rate / number of losses)} x principal x elapsed days ÷ principal Number of turnover days ÷ purchase price per transaction = trading profit / loss is mentioned, but total profit / loss is not mentioned. Further, the calculation method 1 and the calculation method 8 are not mentioned. It is possible to calculate evaluation indexes for various transaction data at each profit / loss level, whether it is total profit / loss, trading profit / loss, or unrealized profit / loss.

(Action of creating evaluation index of transaction data)
There are many methods, but the evaluation index of transaction data is calculated by the following formula, for example. The formulas that decompose the total profit / loss, trading profit / loss, and unrealized profit / loss, which are the objectives, by various evaluation indexes are shown. As a result, various evaluation indexes can be calculated.

[Calculation method 1 (including the turnover rate of winning trades and losing trades)]
Total profit / loss = {(win rate x purchase price of winning trade x winning profit rate) / (principal x elapsed days ÷ number of winning trade turnover days of principal ÷ purchase amount per winning trade) + (loss rate x losing trade) Purchase price x Loss loss rate) / (Principal x Elapsed days ÷ Number of lost trade turnover days of principal ÷ Purchase amount per losing trade)} x Principal x Elapsed days ÷ Principal turnover days ÷ One time Purchase price [Calculation method 2]
Total profit / loss = {(win rate x purchase price of winning trade x winning profit rate / number of wins) + (loss rate x purchase price of losing trade x losing loss rate / number of losses)} x principal x elapsed days ÷ rotation of principal Number of days ÷ Purchase price per purchase [Calculation method 3]
Total profit / loss = {(Win rate x Win profit / Number of wins) + (Loss rate x Loss loss / Number of losses)} x Principal x Number of elapsed days ÷ Number of days of principal rotation ÷ Purchase price per purchase [Calculation method 4]
Total profit / loss = {(win rate x winning profit per time) + (defeat rate x losing loss per time))} x principal x elapsed days ÷ number of days of principal turnover ÷ purchase price per time [calculation method 5]
Total profit / loss = Revenue amount per transaction x Principal x Number of elapsed days ÷ Number of rotation days of principal ÷ Purchase price per transaction [Calculation method 6]
Total profit / loss = Revenue amount per transaction x Principal x Number of elapsed days ÷ Number of rotation days of principal ÷ Purchase price per transaction [Calculation method 7]
Total profit / loss = amount of profit per transaction x number of transactions [Calculation method 8]
Total profit / loss = {(Win rate x Win profit per transaction) + (Defeat rate x Loss loss per transaction))} x Number of trades (Effect of creating evaluation index for transaction data)
By calculating various evaluation indexes of transaction data, it becomes possible to understand how various profits and losses were created. How was the year 2020, what was the year 2019? By period, the difference in the status of the trading data of the traded and the trading data of the unopposed trading, the difference between the a brand and the b brand, etc. will be clarified. What kind of transaction data to handle deals with the trading data extracted in the first to fourth steps.

(Specific example of creating evaluation index of transaction data)
For example, when comparing the evaluation indexes of Mr. A and Mr. B, even if the total profit / loss ratio in 2020 is 10%, which is the same rate, if it is decomposed based on the above formula, Mr. A and Mr. B The difference between buying and selling becomes clear.

Mr. A has a winning rate of 50%, but the winning profit rate is higher than the losing loss rate, and the turnover is effective, but Mr. B has a high winning rate of 70%, but the losing loss rate has become large. , It will be possible to see in detail.

(Display of creation of evaluation index of technical index value)
(Significance of creating an evaluation index for technical index values)
In the place of the holding stock, the technical index value at the time of purchase of the holding stock is displayed, the technical index value in the middle of holding is displayed, and for the trading stock, the technical index value at the time of purchase and sale is displayed. It is possible with.

(Problems of conventional technology)
Normally, the technical index values at the time of purchase or sale need to be managed by oneself, which is troublesome and complicated, and the number of people who can manage them is limited.

(Action of creating evaluation index of technical index value)
It is possible to decide which of the many technical indicators to use, save the technical indicator values at the time of purchase, holding, and sale in the database, and retrieve them at any time. Since it is stored in the database regardless of whether it is conscious or not, it is possible to verify the traded data later from the technical index side.

The information generation unit 3021 is technically linked to actual trading behavior, such as the technical index value at the time of buying, the technical index value at the time of selling, the transition of the technical index value after that, the profit / loss, the profit / loss ratio, and the transition after the sale. Utilize index values.

The display unit 23 of the terminal 2 directly displays and manages the technical index value at the time of purchase, sale, or possession. Therefore, it is possible to automatically give a warning or notification when a similar index value is reached in the past successful cases. It can be used for managing data in the middle of trading, verifying and forecasting data that has already been bought and sold.

(Effect of creating evaluation index of technical index value)
Post-purchase management allows you to understand what the technical indicator values were in the past success stories, prepare for sale in advance, or if you sell at the current level, refer to the past history and use the technical indicator values. It is possible to display the success probability in%.

If it is managed before purchase, it is possible to display the purchase zone and the success probability when purchasing.

Therefore, it can contribute to the purchase decision and the sale decision. In order to realize this, it is important to store data such as the technical index value at the time of purchase, the technical index value at the time of sale, the transition after the sale, the trading profit / loss, and the trading profit / loss ratio in the database, and to retrieve and utilize it at any time. be.

(Specific example of creating evaluation index of technical index value)
At the time of purchase, it is possible to add a function to notify that the stocks sold in the past reach the specified technical index value, and to register the stocks that have reached a certain value in the technical index side in the stock list to be purchased. ..

At the time of holding, the technical index value changes while the price of the stock being held fluctuates daily, so the past history can be referred to to display the success probability when selling, or the stock concerned. It is possible to display zones with a high probability of success.

At the time of sale, the technical index value at the time of sale can be confirmed, and by recording the subsequent transition in the database, it becomes possible to verify whether or not the timing of the sale was correct.

(Definition of creating evaluation indicators for performance data)
In the place of the holding stock, the performance data (expected value and actual value) at the time of purchase of the holding stock is displayed, the performance data in the middle of holding is displayed, and for the trading stock, the performance data at the time of purchase and sale is displayed. It is possible to display it.

(Problems of conventional technology)
Conventionally, performance data at the time of purchase or sale must be managed by oneself, which is cumbersome and complicated, and the number of people who can manage it is limited.

(Action of creating evaluation index of performance data)
It is possible to decide which data to use from among the many performance data, save the performance data at the time of purchase, holding, and sale in the database, and retrieve it at any time. Since it is stored in the database regardless of whether it is conscious or not, it is possible to verify the traded data from the performance data later.

Performance data can be displayed and managed directly at the time of purchase, sale, or holding. Therefore, it is possible to automatically give a warning or notification when the same index value in the past is achieved. It can be used for managing data in the middle of trading, verifying and forecasting data that has already been bought and sold.

For example, the degree of influence on the stock price (the stock price immediately before and the stock price immediately after the announcement, the rate of increase / decrease for one month after the announcement, etc.) when the sales of the forecast figures are revised up by 20% is stored in the database and whenever necessary. Can be pulled out. As a result, the display unit 23 of the terminal 2 displays the movement of the stock price at the time of the upward revision, the movement of the stock price at the time of the same upward revision of the stock in the past, and the movement of the stock price at the time of the same upward revision of the other stock as a comparison target. do. This makes it possible to use it for the next investment behavior and to refer to how to buy and sell.

(Effect of creating evaluation index of performance data)
Post-purchase management allows you to understand how well your performance data was and how it has changed in past success stories, and to prepare for sale in advance.

If it is managed before purchase, it is possible to display the purchase zone and the success probability in the case of purchase.

According to the above, it can contribute to the decision to buy or sell. In order to realize this, it is possible to store data such as performance data at the time of purchase (including forecasts and actual results), performance data at the time of sale, transition after sale, trading profit / loss, trading profit / loss ratio, etc. in a database and retrieve it at any time. is important.

(Specific example of creating evaluation index of performance data)
An example of a reference at the time of purchase is, for example, in the previous example, if the sales are adjusted to increase by 20%, the stock price of the stock that has been increased and adjusted, such as the average percentage increase of the previous stock price and the subsequent three-month high. Since it is possible to clarify the relationship with the rate of increase, it is possible to contribute to the judgment at the time of purchase.

An example of a reference at the time of holding is, for example, when the forecast figures of the performance of the stock held have improved and the sales have been revised upward by 10% compared to the initial forecast, and when the other 10% sales have been revised upward. Since it is possible to immediately refer to how the price movements have been since then, it is possible to contribute to the investment behavior of continuing to hold the stocks held.

An example of a reference at the time of sale is, for example, when the forecasted figures for the performance of the stock held have deteriorated and the 10% sales have been revised downward compared to the initial forecast, and the other 10% sales have been revised downward. Since it is possible to immediately refer to how the price movements have been since then, it is possible to contribute to the investment behavior of deciding to sell the stocks held.

(Definition of creating evaluation indicators for other investment target data)
In the place where the holding stock is displayed, the trading data of other investment targets at the time of purchase of the holding stock is displayed, the trading data of other investment targets in the middle of holding is displayed, and the trading stock is displayed at the time of purchase and sale. It is possible to display the trading status of other investment targets at that time.

(Problems of conventional technology)
In the past, it was usually impossible to know the buying and selling status of other investment targets at the time of purchase or sale.

(Action of creating evaluation indicators for other investment target data)
It is possible to decide which data to use among the trading data of other investment targets, store the trading data of other investment targets at the time of purchase, holding, and sale in the database, and retrieve it at any time. .. Whether you are aware of it or not, it is stored in the database, so you can later verify the traded data and how it was compared to other investment targets.

It is possible to display and manage trading data of other investment targets directly at the time of purchase, sale, or holding.

Therefore, it is possible to automatically warn or notify when the average selling price of other investment targets is reached. It can be used for managing data in the middle of trading, verifying and forecasting data that has already been bought and sold.

(Effect of creating evaluation indicators for other investment target data)
Post-purchase management allows you to see how much profit or loss other investment targets have been in the past success stories and to prepare for sale in advance.

With pre-purchase management, it is possible to display purchase zones and purchase information for other investment targets.

It can contribute to the decision to buy or sell. In order to realize this, data such as purchase information of other investment targets at the time of purchase, sale information of other investment targets at the time of sale, transition after sale, trading profit / loss, trading profit / loss ratio, etc. are stored in the database. It is important to be able to withdraw at any time.

(Specific example of creating evaluation indicators for other investment target data)
(Definition of creating evaluation indicators for other investor data)
In the place of the holding stock, the trading data of the stock of the other investor at the time of purchasing the holding stock is displayed, the trading data of the stock of the other investor in the middle of holding is displayed, and the trading stock is displayed. It is possible to display the trading status of the stock by other investors at the time of purchase and sale.

(Problems of conventional technology)
In the past, it was usually impossible to ascertain the trading status of the stock by other investors at the time of purchase or sale.

(Action of creating evaluation indicators for other investor data)
Decide which data to use among the trading data of the relevant stock of other investors, store the trading data of the relevant stock of other investors at the time of purchase, holding, and sale in the database, and at any time. It will be possible to withdraw. Whether you are aware of it or not, it is stored in the database, so you can later verify the traded data and how it was compared to other investors.

The display unit 23 of the terminal 2 can directly display and manage the trading data of the relevant issue of another investor at the time of purchase, sale, or holding.

Therefore, it is possible to automatically give a warning or notification when the average selling price of the stock of the other investor is reached. It can be used for managing data in the middle of trading, verifying and forecasting data that has already been bought and sold.

(Effect of creating evaluation indicators for other investor data)
Post-purchase management allows you to know what the selling price of the stock was for other investors in past success stories and prepare for sale in advance.

With pre-purchase management, it is possible to display the purchase zone and display the purchase information of the relevant stock by other investors.

It can contribute to the decision to buy or sell. In order to realize this, data such as purchase information of the stock by other investors at the time of purchase, sales information of the stock by other investors at the time of sale, transition after sale, trading profit / loss, trading profit / loss ratio, etc. It is important to store the data in the database and retrieve it at any time.

This time, in this fifth step, there is an evaluation index calculation process, a selection process, and a display process.

The evaluation index creation step includes a calculation process, a selection process, and a display process, and the calculation process has the following three methods.

(Calculation step of evaluation index)
Below, for the calculation steps of the three profit and loss level evaluation indicators,
(1) Calculation of profit / loss level evaluation index (2) Calculation of profit / loss level evaluation index (3) Calculation of profit / loss level stage evaluation index There are three methods, and all of these are collectively calculated step of profit / loss level evaluation index ( Fifth step).

(Difference between calculation of profit / loss level evaluation index and target trading data by profit / loss)
The information generation unit 3021 extracts (or classifies, aggregates, and processes) the trading data to be aggregated, creates the profit / loss level trading data, and calculates the profit / loss level evaluation index. The calculation step of the profit / loss level evaluation index is a step performed after creating the trading data to be aggregated and the component trading data, and has a different purpose from the trading data to be aggregated by profit / loss as described above.

As shown in FIG. 31, the new method of aggregated trading data by profit / loss is a kind of aggregated trading data. For example, trading data is extracted based on winning profit, and the aggregated trading data by profit / loss is obtained. Will be evaluated in the evaluation step. We will take the step of dividing and evaluating the trading data to be aggregated according to the type of profit or loss such as losing loss or trading profit or loss.

On the other hand, the profit / loss level trading data is the trading data aggregated in the process of passing through all the trading data to be aggregated (trading data to be aggregated by profit / loss, trading data to be aggregated by investor, trading data to be aggregated by investment target, etc.). It is trading data that is reprocessed (or classified, aggregated, extracted) in order to calculate an evaluation index based on the standard of profit and loss.

While the trading data to be aggregated by profit and loss targets profit and loss (for example, winning profit), the profit and loss level trading data in the profit and loss level evaluation index sets the aggregation target (for example, investor A) to profit and loss (for example). , Unrealized loss), it is the trading data processed (or classified, aggregated, extracted) to calculate the evaluation index.

Since the former is trading data aggregated by winning profit, both Mr. A's winning profit and Mr. B's winning profit are targeted. On the other hand, the latter is trading data narrowed down only to the trading data of the winning profit to be aggregated, and is processed (or classified, aggregated, extracted) to calculate an evaluation index for evaluating the trading to be aggregated. Trading data.

Three types are illustrated in the step of calculating the evaluation index according to the profit and loss level.

(Relationship between the calculation step of the profit and loss level evaluation index and the old method)
In the first embodiment, a step of acquiring a total profit / loss from trading data and calculating an evaluation index with reference to the total profit / loss is shown. A specific example of the evaluation index is shown. The evaluation index calculation process of acquiring basic data from trading data and calculating the evaluation index by referring to the basic data is presented.

38 and 40 are diagrams showing a calculation example of the evaluation index according to the present embodiment. FIG. 39 is a diagram showing extraction of winning profit level data according to the present embodiment.

The calculation step of the profit / loss level evaluation index is to extract (or classify, aggregate, process) the trading data to be aggregated and the component trading data, and create the profit / loss level trading data by the information processing system. It is different from calculating the evaluation index using the evaluation index calculation table or the like.

The relationship between the old method and the present embodiment will be described.

In the old method, acquiring the total trading profit / loss from the trading data is the step of acquiring the basic data. In the old method, the evaluation index is calculated by acquiring the total trading profit and loss and decomposing it. That is, in the old method, the evaluation index is calculated with reference to the total trading profit / loss. It is constructed on the premise of the trading data of investor A, and is a method of calculating the evaluation index by a formula.

In the present embodiment, the information generation unit 3021 extracts (or classifies, aggregates, processes) the trading data to be aggregated, and further extracts (or classifies, aggregates, processes) the trading data in the process of trading data for each component. Then, for the trading data, create profit / loss level trading data (it is possible to have it in the previous process), and calculate the evaluation index using the evaluation index calculation table etc. based on the trading data. Execute the step. That is, the information generation unit 3021 is an epoch-making system in that the evaluation index is calculated based on the collaborative work of the series of linked computers, and the point that they are linked is not disjointed.

The former decomposes the total trading profit and loss and calculates the evaluation index based on its components, while the latter calculates the evaluation index from the trading data that has undergone a series of work processes, so management items can be increased as described later. Not only transaction data (trading data in a narrow sense), but also performance data and technical data, as well as all items that affect the investment results of investors, such as trends of other investors and price movements of other investment targets, are captured. The significance of making it possible is great (described later). The former is an example of FIG. 39 (the evaluation index is calculated by decomposing the mathematical formula). The latter is an example of FIG. 40 (evaluation index is calculated from trading data).

The former is a decomposition approach. The latter is a database approach to trading data. Even if the same evaluation index is calculated, the approach is different.

For example, even in the calculation of the evaluation index of Mr. A's winning profit margin (rate of return when winning in Fig. 39), the former finds the total value of winning profit (26.85 million yen in Fig. 39) and wins profit. It is calculated by dividing by the total trading value (40.92 million yen in Fig. 39). On the other hand, in the latter, the trading data is gradually narrowed down to the winning profit trading data in the second step, the third step, and the fourth step, and is calculated from the trading data using an evaluation index calculation table or the like (Fig. 39, 40 and 111).

It has become possible to handle various items under various extraction conditions and classification conditions because this database linkage technology has made it possible to calculate evaluation indexes in a series of steps. By adding these evaluation indexes to the items next to the trading data, all the series of work can be done on the database even in the subsequent process, it is not disjointed, the meaning of the connection is great, and this greatly changes the technical level. rice field.

Of course, as shown in FIG. 40, the winning profit margin may or may not be added to the winning profit trading data, but adding the item has the advantage that the winning profit margin for each trading becomes clear. It is also assumed that items such as other evaluation indexes and basic data will be added to the trading data and processed. Further, as shown in FIG. 40, it is possible to easily display the totalization for each component or the totalization for the whole.

(Problems of conventional technology)
In the old method, for example, when evaluating the total trading profit / loss, the approach is to decompose the total trading profit / loss as in the first embodiment, whereas in this embodiment, the trading data is the trading data in which the trading profit / loss is fixed. Only is extracted (or classified, aggregated, processed), and various evaluation indexes are calculated by the information processing system for the trading data. Specifically, when evaluating the total winning profit, the evaluation index of the total winning profit is calculated by the decomposition formula as shown in FIG. 39, and the evaluation index is based on the trading data of the total winning profit as shown in FIG. 40. The difference becomes clear when the calculation of is performed.

In the example of the trading profit / loss step, the trading profit / loss level is based on the trading data to evaluate the trading profit / loss. Create trading profit / loss level trading data (even if you have it in the previous process) while processing based on the trading data extracted (or classified, aggregated, processed) from the trading data to be aggregated. The evaluation index can be flexibly calculated by the information processing system based on the trading data. For example, when the winning profit is evaluated as shown in FIG. 40, the winning profit level trading data is used as the basis. The evaluation index can be calculated flexibly based on the winning profit trading data. And the structure is easy to process in the database.

(Action of calculation step of profit / loss level evaluation index)
The information generation unit 3021 extracts (or) the trading data according to the target profit / loss based on the aggregation target trading data and the component-specific trading data created in the aggregation target trading data creation step. (Classification, aggregation, processing), processing according to the level is performed, and the evaluation index is calculated by the information processing system from the profit / loss level trading data.

(Effect of calculation step of profit / loss level evaluation index)
Since various evaluation indexes can be calculated by the information processing system using a form determined by using an evaluation index calculation table or the like, it is easy to automate and anyone can calculate. Since everything is linked in the database, it is related to investment profit and loss, such as technical index values and corporate performance data that link management items with trading data, behavior of other investors on the same issue, and trends of other issues on the same purchase date. The effect of being able to incorporate various items to be evaluated as an evaluation index brings about a remarkable effect. Furthermore, by taking a series of steps of creating trading data to be aggregated, trading data by component, and creating profit / loss level trading data, the trading data to be worked on is narrowed down, and what is evaluated and how. If the information processing system is instructed to proceed, the effect of being able to handle various types of trading data produces immeasurable effects. The trading data subject to aggregation by period and the trading data subject to aggregation by investment target are examples.

Furthermore, compared to the conventional technology, by creating profit / loss level trading data, evaluation indexes for each trading can be calculated, items can be extracted (or classified, aggregated, and processed), and the range of application of the cut is expanded.

(Specific example of calculation step of profit / loss level evaluation index)
I will explain it later.

There are the following three types of steps for calculating the profit and loss level evaluation index.
(1) Calculation of profit / loss level evaluation index (2) Calculation of evaluation index by profit / loss level (3) Calculation of profit / loss level stage evaluation index Refer to the explanatory diagram of the calculation step of the evaluation index (Fig. 107).

(Definition of calculation of profit / loss level evaluation index)
There are various types of profit and loss calculated from trading data. For example, in the case of unrealized profit, trading data is extracted (or classified, aggregated, processed) at the unrealized profit level. In that case, the trading data created in the 4th step is extracted from the trading data that is unopposed and profitable, and the unrealized profit level trading data is added by adding items such as the unrealized profit ratio and the number of elapsed days. The calculation of the evaluation index based on the trading data created by the information processing system is defined as the calculation of the profit / loss level evaluation index (unrealized profit in this example).

(Problems of conventional technology)
If it is a conventional calculation method, there is no step of creating trading data. This technology clarified the target to be evaluated and the profit and loss to be targeted at the creation step. Since the purpose of buying and selling investment products is mainly to improve profit and loss, trading data is extracted (or classified, aggregated, processed) based on the profit and loss that should be targeted, and the evaluation index is based on the trading data. By using it to evaluate and compare the aggregated objects, the whole series of flows was connected, and it became possible to proceed to the next step.

(Action of calculation of profit / loss level evaluation index)
The information generation unit 3021 extracts (or classifies, aggregates, processes) the trading data at the profit / loss level based on the aggregated trading data created by the information processing system in the aggregation target trading data creation step, and the profit / loss level. Create trading data and calculate the profit / loss level evaluation index in the information system based on the profit / loss level trading data.

(Effect of calculation of profit / loss level evaluation index)
By calculating the evaluation index based on the extracted (or classified, aggregated, processed) trading data for the target profit and loss, it is possible to calculate an appropriate evaluation index for the profit and loss to be aggregated.

(Specific example of calculation of profit / loss level evaluation index)
When calculating the trading profit / loss level evaluation index, the information generation unit 3021 extracts (or classifies, aggregates, and processes) only the trading data whose profit / loss is confirmed from the trading data to be aggregated, and the trading profit / loss ratio and the number of days of holding of the trading issue. , Win / loss, etc. are added to calculate the trading profit / loss level evaluation index. For example, the information generation unit 3021 extracts (or classifies, aggregates, and processes) only the confirmed trading data of Mr. A's trading data, and the trading profit / loss level such as the winning percentage, the trading profit / loss ratio, and the number of trading times obtained from the extracted trading data. Calculate the evaluation index.

(Definition of calculation of evaluation index by profit / loss level)
There are various types of profits and losses calculated from trading data. For example, when trading data is extracted (or classified, aggregated, processed) by the information processing system at the unrealized profit level, trading is unopposed and profitable. Extracting data by profit / loss level, such as extracting (or classifying, summarizing, processing), and in the case of trading profit, extracting (or classifying, summarizing, processing) trading data that is trading in the opposite direction and is profitable. , Defined as the calculation of valuation index by profit / loss level.

(Issues in calculating evaluation indicators by profit and loss level)
In the calculation of the profit / loss level evaluation index by the information system, it is assumed that multiple evaluation indexes are calculated for one profit / loss level, but in the calculation of the profit / loss level evaluation index, multiple evaluation indexes are calculated for each profit / loss level. Is assumed to be calculated by the information processing system (see the explanatory diagram (FIG. 107) of the calculation step of the evaluation index).

(Action of calculation of evaluation index by profit / loss level)
The information generation unit 3021 extracts the trading data by profit / loss level by the information processing system based on the trading data to be aggregated and the component trading data created in the step of creating the trading data to be aggregated, and the trading data by profit / loss. Is created, and the evaluation index for each profit / loss level is calculated by the information processing system using the trading data.

(Effect of calculation of evaluation index by profit / loss level)
The calculated evaluation index is different between the trading data at the trading profit / loss level and the trading data at the unrealized profit level, and the target profit / loss is also different. Therefore, by classifying both and calculating the evaluation index separately, a plurality of profit / loss level trading data can be created, and the level of evaluation of the aggregation target can be improved. In the case of the above-mentioned calculation of the profit / loss level evaluation index, in the case of trading profit / loss, the trading profit / loss level trading data is targeted, whereas in the calculation of the profit / loss level evaluation index, in addition to the trading profit / loss level trading data, Since multiple profit / loss level trading data are created, such as creating unrealized profit / loss level trading data, evaluation indexes are widely calculated, and there is an effect that the operation steps after the sixth step can be deepened.

(Specific example of calculation of evaluation index by profit / loss level)
For example, the winning profit trading data is extracted from Mr. A's trading data (winning profit (buying price (or market price at time A) <selling price) among the confirmed trading), processed, and the winning profit ratio etc. is obtained from the trading data. Calculate the evaluation index. Then, the unrealized loss trading data is extracted from Mr. A's trading data (buying price (or market price at time A)> trading data at time B of undetermined trading) to calculate the unrealized loss rate, and each level of profit or loss is calculated. Calculation of the evaluation index is a step of calculating the evaluation index for each level. Any of the trading data created up to the 4th step can be created, so if it is processed by a computer, it will be quick.

(Relationship with conventional technology for calculation of profit / loss level stage evaluation index)
Even in the old method, in the first embodiment, the calculation of the evaluation index changes according to the level stage (detail level) of the profit and loss, and since the evaluation index changes, the evaluation is also performed step by step. Further, in the first embodiment, various evaluation indexes according to the degree of detail are targeted for evaluation, and the calculation formula of the degree of detail 5 is displayed.

In the old method, the approach method is expressed in a calculation formula. For example, as shown in FIG. 39, the total winning profit is decomposed into elements to calculate the evaluation index. On the other hand, in the new method, the profit / loss level step evaluation index is calculated step by step from the profit / loss level trading data as shown in FIG. 41 (see the explanatory diagram of the calculation step of the evaluation index (FIG. 107)). For example, the evaluation index is calculated step by step according to the profit / loss level, such as creating trading profit / loss level trading data, extracting winning profit level trading data, and further dividing the winning pattern level trading data into three types. To go.

Further, in the calculation of the evaluation index for each profit / loss level, a plurality of trading data for a plurality of profit / loss are created, and a plurality of evaluation indexes are calculated. This profit / loss level staged evaluation index evaluates the profit / loss level step by step, and by referring to the gradually deeper and more detailed evaluation index, it is possible to evaluate the aggregation target in more detail step by step. It is a technology that goes one step further.

(Definition of calculation of profit / loss level stage evaluation index)
(Profit and loss level stage evaluation index)
FIG. 41 is a diagram showing a profit / loss level stage evaluation index according to the present embodiment. The information generation unit 3021 looks at the trading data with comprehensive power (first level), extracts (or classifies, aggregates, and processes) the trading data depending on whether or not the trading data is counter-trading (second level), and the trading data. Data is extracted (or classified, aggregated, processed) according to whether or not it is profitable (third level), and the trading data is further divided into patterns and extracted (fourth level). Trading data is processed and created by a method of extracting (or classifying, aggregating, and processing) trading data step by step, and each evaluation index is calculated. However, the above example is merely an example, and may be divided into two stages, three stages, a second level, or another method.

(Issues in calculating profit / loss level stage evaluation indicators)
In the calculation of the evaluation index by profit and loss level, the evaluation index was calculated by profit and loss level, but in the profit and loss level stage evaluation index, the trading data by profit and loss is extracted (or classified, etc.) for each of the first level, the second level, the third level, etc. (Aggregate and process), and the evaluation index is calculated by the information processing system for each stage. As a result, the evaluation index is calculated by the information processing system by sequentially calculating detailed evaluation indexes instead of being disjointed.

(Action of calculation of profit / loss level stage evaluation index)
The information generation unit 3021 extracts (or classifies, aggregates, processes) the trading data for each profit / loss level based on the trading data to be aggregated created in the aggregation target trading data creation step, and aggregates by profit / loss step by step. Target trading data is created, and the evaluation index for each profit / loss level is calculated by the information processing system for each stage.

(Effect of calculation of profit / loss level stage evaluation index)
When evaluating the trading situation, the number of evaluation indicators increases as you progress from the 1st level total profit / loss stage to the 2nd level trading profit / loss level, the 3rd level winning profit level, and the 4th level winning pattern level. , Since the evaluation index that narrows down the target in more detail is calculated by the information processing system, the fine-grained evaluation index can be calculated step by step.

The higher the level, the lower the importance, while the higher the level, the better the overview and the overall picture, and the lower the level, the more detailed the part. For example, it is possible to compare the trading data of winning trades with the trading data of losing trades, and to compare changes in corporate performance and changes in technical indicators between both trading data.

(Specific example of calculation of profit / loss level stage evaluation index)
FIG. 42 is a diagram showing a specific example of calculation of the profit / loss level stage evaluation index according to the present embodiment by the information processing system. FIG. 42 shows an example in which the total profit / loss was 22.89 million yen with a principal of 500,000 yen.

The total profit was 22.89 million yen at the first level, but the actual profit and loss is clear when the trading profit / loss level is 16.23 million yen, the winning profit is 26.85 million yen, and the losing loss is 10.47 million yen. become.

For example, it can be seen that FIGS. 39 and 40 refer to the third winning profit level of FIG. 42 and evaluate only a part of the whole.

By calculating each evaluation index, the winning profit rate of 67%, the losing loss rate of -11%, etc. will be clarified in stages, so that the overall picture of the trading data to be aggregated and each part can be accurately grasped. Will be possible.

In the case where the total profit / loss was 22.89 million yen at 500,000 yen, the total profit / loss trading data was created by the information processing system at the first level, and the confirmed trading data and the unconfirmed trading data were separated, and the finalized trading was confirmed. The data is further divided into winning profit trading data and losing loss trading data, and undetermined trading data is further divided into unrealized profit trading data and unrealized loss trading data, and further divided by pattern. As a result, a plurality of useful evaluation indexes are calculated by the information processing system for each trading data. As you take steps, the actual state of profit and loss becomes clear. By calculating each evaluation index, the winning profit rate of 67%, the losing loss rate of -11%, the unrealized profit rate of 88%, the unrealized loss rate of -5%, etc. are clarified step by step. This makes it possible for the information processing system to accurately grasp the overall picture of the trading data to be aggregated and the component trading data and each part (see the explanatory diagram of the evaluation index calculation step (FIG. 107)). ).

Among the calculation steps of the evaluation index by the information processing system, there are a calculation process, a selection judgment process, and a display process.

(Significance of the evaluation index calculation process)
The basis for calculating the evaluation index by the information processing system is the trading data extracted (or classified, aggregated, processed) in the process up to the fourth step. Since the trading data is created according to the task, the data necessary for the task is complete, and the evaluation index calculated by the information processing system based on the data is also derived according to the task. It becomes an evaluation index.

For example, the winning rate of trading by issue A in 2020 and the trading profit composition ratio of issue A are the trading data subject to aggregation by period in 2020, the trading data by component for each issue, and the trading profit / loss level trading data. It is an evaluation index that can be derived for the first time. Everything is working together. That is why the information processing system calculates an evaluation index that can solve the problem. Further, these evaluation indexes such as winning percentage are evaluation indexes derived from transaction data, but items necessary for the evaluation target are selected as management items in the trading data. For example, in the case of a brand, it may be a technical index value or a corporate performance, and such an index is also a kind of evaluation index, and is an evaluation index that can be utilized in subsequent operation steps.

Moreover, what is particularly important is the technical index value managed there, for example, the technical index value is not a mere technical index value, but a technical index value managed in association with purchase data or the like, or performance data. Compared to the case where it is simply linked to the brand information, the technical index value will move while holding it after purchase, and if the sell signal lights up, a warning will be issued, or information that has been disjointed until now. Play a role of connecting. The information that can be done and managed is completely different between the link with the brand information and the link with the purchase information. This point is difficult to understand, so supplementally, the stocks that you manage (hold) are automatically connected to technical index values, candlesticks, chart data, etc. For example, the RSI index of the stocks you own is 80. If it exceeds%, a signal will be generated, and if a candlestick has a tangent line, a signal will be generated very easily. It is possible to show it on the chart that you see every day, and on the dashboard, you can express it like the technical index value of the stock you own today, and you can use it in various ways by linking it with trading data. For example, a brand bought in a place where there is a feeling of overheating at the time of purchase can issue a warning sign to encourage an early loss cut. In addition, being able to manage means that technical data is stored in a form linked to trading data. This will become a great weapon later. In other words, Investor A records that the tendency of buying and selling is to buy when this technical index value becomes like this and sell when this happens, so the failure overlaps and it is the same. It is also possible to issue a warning sign to encourage loss cuts or discourage profit taking when making such a mistake. This can incorporate not only technical index values but also various items related to investment profit and loss, such as corporate performance data, behavior of other stocks of the same stock on the same purchase date, and trends of other stocks on the same purchase date. It is one of the major features of the information processing system that can be made.

(Problems of conventional technology)
The evaluation index is also mentioned in the first embodiment, and various evaluation indexes are also explained. However, these evaluation indexes are evaluation indexes derived from trading data in a narrow sense. The calculation of winning / losing winning percentage and winning profit margin is also based on evaluation indexes derived from trading data in a narrow sense such as purchase date, brand, purchase price, sale date, sale price, and transaction volume. However, in Embodiment 4, in addition to these evaluation indicators, charts, technical indicators, trends in corporate performance, and other investors that can be linked to a set of stocks and dates such as purchase date and sale date. It makes it possible to incorporate various items related to investment profit and loss, such as the behavior of the same issue and the trends of other issues on the same purchase date, as evaluation indicators. It is a very potential technological innovation that can be used to change trading behavior and advice. This information is generally some information, but it is not tied to purchase information. Only when it is linked to the purchase information (relationship), the purchased brand and this information are linked, and a special meaning comes out. The fact that information on technical index values, company information, behavior of the same stock of other investors, trends of other stocks on the same purchase date, and purchase information are linked means that such information can be used freely for post-purchase management. By verifying when the buying and selling is finished later and keeping these records, it becomes possible to investigate the points and weaknesses that are always stumbling. It is a very impactful technological innovation that dramatically expands and deepens advice and diagnostic capabilities. In addition, although there are various evaluation indexes, the winning percentage of buying and selling of Mr. A's stock can be calculated relatively easily by the information processing system, but the winning percentage of buying and selling by stock A of the Daytre investment type group in 2020 is. what%? It is necessary to properly derive from the database for the problem. Furthermore, it is indispensable to link with the database, and it is impossible to manage the RSI at the time of purchase and the RSI at the time of sale of the A brand of the day trading investment type group in 2020. In the fourth embodiment, since the cooperation is consistent, if the management items are added in the first step, they are managed in this step of the fifth step, and they are also managed by the advice of the tenth step. It is possible to provide advice by the information processing system using the index.

(Action of evaluation index calculation process)
With the creation of trading data to be aggregated by period for the trading data to be aggregated by investment type of Daytre, the information processing system is used to create the trading data to be aggregated by period of the Daytre type group in 2020 with 2020 as the extraction condition. Trading profit / loss level Create trading data (even if you have it in the previous process), create trading data that is a component of issue A, derive the number of trading and the number of wins from the trading data, and derive the winning rate. Therefore, it is calculated by the information processing system. In addition, the RSI at the time of purchasing the A issue of the Daytre investment type group in 2020 is managed as one of the components when creating the trading data (it is included in one item of the trading data), and it is immediately relevant. It can be derived when the information processing system is needed. The same applies to corporate performance, the behavior of other stocks of the same stock by other investors, and the trends of other stocks on the same purchase date. These are not just RSI, corporate performance, behavior of the same stock of other investors, trends of other stocks on the same purchase date, etc., but the evaluation index associated with the investment profit / loss that is the purpose of the trading data set is the information. It is one of the evaluation indexes with the purpose of being calculated by the processing system.

Explaining what it means to manage the RSI at the time of purchase, the purchase date is May 1, the stock price of issue A at that time is 500 yen, and the RSI is 20%. After that, it is assumed that the stock price reached 550 yen and the RSI reached 50% on June 1st with the passage of time. These numbers can be managed by individuals if they want to, but unless they really like stocks, they can't be managed and are very cumbersome. While there are a huge number of other technical index values, ordinary people do not know what to choose. So it's best to leave this to the computer. The RSI at the time of purchase is managed, and the movement of the RSI according to the daily price movement from there can be grasped, which also determines the RSI at the time of sale. It is very important that such information is recorded daily. The main reason for linking with purchase data is that it will be possible to record in this database and later give advice and diagnosis using it, and each function will be dramatically improved.

(Effect of evaluation index calculation process)
Up to the 4th step, the target trading data is determined, and since it is an evaluation index derived from the profit / loss (or average trading profit / loss ratio (ROI average)) that is the total result of the trading data, the evaluation necessary for solving the problem. The index can be calculated by the information processing system, and a wide and deep evaluation index that is in line with the problem is calculated by the information processing system. In addition, the RSI and corporate performance at the time of purchasing the A stock of the day trading investment type group in 2020, the behavior of the same stock of other investors and the trends of other stocks on the same purchase date are also linked to the transaction data, so there are various things. Can be used. Therefore, the RSI, which was 20% at the time of purchase, can be managed to change to 40%, 50%, etc. during daily stock price updates. Then, it was sold at about 50% (stock price rose 10%), but after that, the stock price rose further, RSI 80%, stock price rose 40%, and in the end, it was a big loss of profit. It will be recorded in. These data will later become assets for investors, and the rules of success and failure will be set, and it will be a technological innovation that can greatly contribute to the visualization of investment.

(Specific example of evaluation index calculation process)
(Specific example 1)
For purchase data with a technical index RSI of 20% or less, the issue of the winning rate, winning profit rate, and stock composition ratio of trading profits that were traded in the opposite direction is first addressed from the trading data to be aggregated at the time of purchase. Extracts trading data of 20% or less, creates trading profit / loss trading data, creates component trading data aggregated by issue by the information processing system, total value of trading profit and composition ratio by issue, It is obtained by calculating the number of trades, the number of winning trades, and the winning profit margin of the winning trades data. It is a step to calculate an evaluation index that is very difficult or impossible to calculate without cooperation with a database.

(Specific example 2)
For the issue of comparing the difference between the winning rate, the winning profit rate, and the trading profit / loss ratio between those who buy / sell within 5 days and those who buy / sell for 120 days or more, the trading profit / loss Level trading data is created by the information processing system, the holding period item from the purchase date to the sale date is added to the database as processed data by the information processing system, and the trading data with a holding period of 5 days or less and the holding period of 120 days Each of the above trading data is compared by calculating the winning rate, the winning profit rate, and the trading profit / loss rate.

(Specific example 3)
To create article data such as what kind of characteristics the buying and selling of people who are buying and selling have on Twitter, use the trading data to be aggregated by medium, extract with "medium = four seasons report", and then It is obtained by comparing the obtained evaluation index with the evaluation index of all investors.

(Specific example 4)
Specific example 2 can be used as article data as to which of the short-term trading traders and medium- to long-term investors will win.

(Specific example 5)
Specific example 1 can be used as article data on the RSI, which is famous as a technical index, and how the winning percentage is.

(Specific example 6)
Subsequent trading behavior of other investors on the same stock and the same purchase date can be one of the evaluation indicators.

(Specific example 7)
One of the evaluation indexes can be the ranking of the rate of increase / decrease of other stocks on the same purchase date and the comparison with other stocks during the holding period.

(Definition of evaluation index)
The evaluation index is an index for evaluating (or comparing, ranking, diagnosis, advice, etc.) the target (in the case of an investor, the investor, in the case of an investment target, the investment target), and affects the investment profit / loss of the target. The element to be given is defined as an evaluation index.

(Problems of conventional technology)
In the first embodiment, the evaluation index is calculated from trading data (trading data in a narrow sense), for example, turning power, winning rate of return, losing loss rate, trading profit / loss, rising / falling rate of owned stocks, principal increase / decrease rate, etc. In the indicators to be used, the factors that directly affect the trading profit and loss were the main ones. There is no doubt that these evaluation indicators are important, but there are other factors that affect investment profit and loss, and there was the problem that they were not covered. For example, the timing of buying and selling an investment target. Just changing the timing can be a loss or a profit. This is not included in the previous metrics. The purpose of calculating the evaluation index is to appropriately evaluate the target and calculate the evaluation index to improve the investment profit / loss, which is the purpose. The more factors that influence the investment profit / loss, which is the purpose, are incorporated, the more appropriate evaluations can be made, and the ability to make proposals and make diagnostics for improving investment profit / loss will increase. Factors that affect investment profit / loss include changes in trading timing and fundamentals of investment targets, as well as investment behavior of other investors and price movements of other investment targets. By adding these indexes to the model of the information processing system as evaluation indexes, it is possible to more appropriately evaluate the target.

(Action of evaluation index)
Up to the fourth step, the target trading data has been determined by the information processing system, and various evaluation indexes are calculated from the trading data by the information processing system. For example, in the case of the trading profit / loss ratio, the trading profit / loss ratio of each trading is determined by the investment profit / loss / purchase amount of each trading, and the average trading profit / loss ratio in the trading data can be obtained by obtaining the average value. For example, if the RSI value at the time of purchase is determined at the time of purchase and is in possession, the RSI value of the relevant issue on the current date is managed on the database, so that value is constantly updated in the information processing system every day. It will also be recorded. If the RSI value at the time of purchase is 40% and the current RSI value is 80%, it will be managed as one of the evaluation indexes in the information processing system. If the RSI value exceeds 80%, it is possible to emit a warning signal. Other evaluation indexes also have their own calculation methods. These calculation procedures can be centrally managed by managing them in a calculation table or the like. In the previous example, trading profit / loss ratio = investment profit / loss of each trading / purchase amount of each trading = (sale amount-purchase amount) / purchase unit price x purchase quantity and average trading profit / loss ratio of trading data = trading of the trading data The information processing system calculates various evaluation indexes according to each rule of the average value of the profit / loss ratio.

(Effect of evaluation index)
The examples of RSI values given above have unthinkable effects at the time of Embodiment 1. By incorporating charts, technical index values, investment behavior of other investors, price movements of other investment targets, etc. into the evaluation index of the information processing system, the evaluation index for the timing of buying and selling can be managed by the information processing system. In addition, the merit of being able to place an element that has a great influence on the investment results of the investment target, such as changes in the fundamentals of the investment target, such as business performance, in the management of the information processing system is immeasurable. In the end, investors have to make their own judgment when displaying charts, technical index values, and corporate performance. However, the technical significance of being able to link these evaluation indexes with trading data in the information processing system is extremely significant. By adding technical index values, corporate performance values, and evaluation indexes related to trading, it is a technological innovation that has a great impact on a series of actions such as investor evaluation, investment target evaluation, advice and diagnostic ability, comparison, and ranking.

(Specific example 1 of evaluation index)
Even one of the above RSIs has great technical significance incorporated into the evaluation index of the information processing system. It means that any technical index value can be incorporated, and the technical index value at the time of purchase and the technical index value during, at the time of sale, and after sale are accumulated together with these trading behaviors. Ordinary investors are not aware of this, but in the information processing system, investors are not aware of this, and by recording these figures at the time of purchase or sale, the investor buys and sells. It means that it will be possible to read the trends and the usual patterns of investors. This is a technology that will be a breakthrough in the investment world. Things that cannot normally be managed can now be managed and can be used in various ways.

(Specific example 2 of evaluation index)
The same applies to corporate performance. Changes in fundamentals must influence buying and selling, which is also quite difficult. Changes in corporate fundamentals, such as quarterly settlement of accounts and revisions during the period, are commonplace, and it is not known when they will occur, and it requires considerable experience and know-how to determine what kind of impact they will have. However, in the information processing system, the fourth embodiment has evolved so that these changes in corporate performance can also be incorporated into the evaluation index and can be utilized for evaluation, advice, diagnosis, and the like. For example, the company forecast figures for sales this year (for example, if it is September 2020, if it is a company with a settlement of accounts for the fiscal year ending March 2021, the fiscal year ending March 2021), can be incorporated into one of the evaluation indicators. Just do it. In the September stage, it was 100 billion yen, it was revised upward in December to 120 billion yen, and it was revised upward again in March to 140 billion yen. You have to manage the purchased stocks yourself. However, in the information processing system, it means that this change can be incorporated as one of the evaluation indexes. This year's sales forecast at the time of purchase was 100 billion yen, and with the passage of time, this year's sales forecast was added as an evaluation index along with the market value evaluation, so it was updated to 120 billion yen in December and 140 billion yen in March. It will be updated in yen and will be updated to 150 billion yen in May. It will be updated with daily update information, and past history will be accumulated at any time. This is a very epoch-making thing, and it means that it will be possible for investors to leave the information processing system to some extent troublesome such as technical analysis and checking of corporate performance trends. ..

(Specific example 3 of evaluation index)
In addition, the behavior of other investors is one of the factors that have a great influence on investment profit and loss. For example, suppose that there is a stock with a stock price of 800 yen at present, and that many other investors had purchased the target for 850 yen a month ago. This is called selling pressure, and it is common in the market that the closer you get from 800 yen to 830 yen or 850 yen, the more pressure you want to sell and the price movement stops. Until now, this was also left to individual judgment and symbolized the difficulty of stocks. This is a typical example of investment profit and loss being influenced by the behavior of other investors. In the information processing system, when a stock is purchased, the stock, purchase date, purchase stock price, etc. are recorded, and behind the scenes, the actions of other investors are also recorded. It means that the past purchase history of the purchased issue is also taken, and it means that the investment behavior of other investors in the past of the issue is grasped as well as the purchase of the issue. Therefore, it is one of the features of the information processing system that such selling pressure is around 850 yen, which can be sufficiently predicted. Because the trading data is recorded in the recording unit as trading data to be aggregated by investor, it has the flexibility to add such information of purchased stocks as an evaluation index. The method of grasping this with the information processing system may be set so as to go to the past purchase history of the brand at the time of purchase. Specifically, it is sufficient to indicate whether or not there is a price range in which a large amount of trading value has been collected in the past month in a price range higher than the current stock price of the stock. It is also possible to create and manage a selling pressure zone table for each issue. Then, if the table is managed as an evaluation index and referred to, the zone can be immediately grasped and displayed by the information processing system, and attention can be paid to it.

(Specific example 4 of evaluation index)
In addition, the price movements of other stocks are one of the factors that have a great influence on investment profit and loss. The funds that flow into the market are limited to some extent, and in particular, the funds circulate, the A brand is sold, and the B brand is bought with the sold funds on a daily basis in the market. It will be traded. Therefore, it is not enough to manage even the stocks that you own, but the trends of the stocks that you do not own or the trends of the entire market always affect the investment profit and loss. As for the trends of other stocks, the information system collects information behind the scenes, so this trend can also be managed, and the price of the stocks held has increased by 10%, but other investors at the same time It also has information such as that the purchased B issue has increased by 30%, and it is possible to follow the price movement of the issue that has increased the most from the purchase date, which is also the trading data like the RSI value etc. It is one of the functions added to the information system as a result of the fusion of market data.

(How to link technical indicators with trading data)
There are two main methods for linking technical indicators and corporate performance with trading data. One is to link with stock information, which is especially often used for managing stocks held, and when you click on a stock you own, you can link charts, technical indicators, corporate performance, stock news, etc. of the stocks you own. This is the case. This is the first method, which is usually common. The second method refers to a method in which the stock and date (date and date of purchase, sale, date during the holding period, date and date after sale, etc.) and trading data are linked in some way. One method is the method shown in FIG. 91, but other methods linked by brand and date fall into this category. For example, what is the difference between being tied to a brand and the date of purchase and being tied to a brand? If it is linked to a brand, as you saw earlier, clicking on the brand will output and display information about that brand. On the other hand, if the purchase date is linked to the brand, the RSI value of the brand's purchase date and the corporate performance of the purchase date can be output and displayed. It is a method that makes it possible to express the RSI value and corporate performance of. This refers to the method in which the current year's sales forecast of the company forecast on the purchase date, the current year's sales forecast of the company forecast on the sale date, and the current year's sales forecast of the company forecast during the holding period are managed. If it is linked to the stock information, this should be displayed as stock information, and if it is linked to the stock and date, trading data, it is as personalized information (information transmitted only to investor A). It should be displayed. Investor B, who purchased the same brand on a different date, will see a different display. Here, this method is defined as a method (personalization method) in which a brand, a date, and trading data are linked.

(Significance of calculation of evaluation index of technical index value)
Technical indicators are commonly used quite often in the stock market. There are many types of technical index values, such as judgment of whether the stock price is heating up, judgment of purchase time, judgment by automatic trading, and so on.

(Problems of conventional technology)
Even if you know that these technical indicator values are important, they are very difficult to manage, there are too many types, you do not know which one to use, there are many deceptions, you can not use it, everyone can use it. For example, there are many people who avoid it because of the complexity and difficulty of management, such as when it becomes ineffective. Stocks are also one of the major factors that make us feel difficult. However, these fields are where computers come into play, and by recording them daily on a computer, it is a good material for machine learning and gradually improving accuracy. However, this time, we will not go into it deeply, and it will be a technical index that anyone can use even if we manage after purchase, holding, and sale by using the technical index as one material. However, even with the same technical index association, the date and the issue are associated with each other, and the issue is associated with the issue and displayed. Technical indicator values are often displayed in association with this stock. You can also see technical indicators and corporate performance on the management screen on the stock chart. Information linked to a brand, these are conventional technologies, and the issues of these conventional technologies must be managed by each person even if technical index values etc. are posted, so it is a very ordinary person. Is unmanageable. Just because the technical indicators are displayed along with the stocks held on the management screen, even if there is information, it is not tied to your own purchase, so it is not personalized. However, if it is linked to the purchase date or sale date, it can be used for advice and diagnosis based on the timing of the purchase or sale, and it can be expected to have a very large effect that it can be used for comparison, ranking, evaluation, etc. It works, functions, and works completely differently from what is associated with a purchase or sale.

(Action of calculation of evaluation index of technical index value)
It is important as a preparatory step to make the technical index value a control item in the first step. Any technical index value can be used, but here it is RSI. Since the purchase date and brand are determined when a brand is purchased, if an RSI table that manages the purchase date and RSI of the brand is prepared and associated with trading data, the data in this table can be imported (database related). Figure (see Figure 91) (not limited to this method, including all cases where the issue is associated with the purchase date (or sale date) and the value of the technical indicator). As a result, the linking of trading data and RSI is completed, and daily RSI for each issue can be managed as an evaluation index as one of the evaluation indexes of the fifth step. By linking the purchase date with the brand, it is possible to manage the RSI 10 days after the purchase date. The RSI is managed at the time of sale, and the same is true after the sale. The RSI process from buying to selling is also managed for each issue. In other words, it is an image that one important evaluation index increases.

(Effect of calculation of evaluation index of technical index value)
What will change when we can manage this RSI? First, the RSI from purchase to sale is managed on a daily basis. This kind of management can only be done if you are very fond of stocks. The average investor is unaware of this. However, when the daily RSI is tracked on a computer, it is easy for the information processing system to issue a warning signal when the zone is generally said to exceed 80%. Furthermore, even after the sale, if the RSI, which had risen to 80% at the time of sale, has fallen below 20%, the RSI of the A brand sold the other day is 20 because it is managed by the information processing system. It has been less than%. It may be time to purchase again, why don't you consider it? "It's too complicated for users to manage, but if the computer emits a danger signal or a purchase signal, it will be very convenient. Further, if the computer is used, these pieces of information are sequentially stored. There are cases where it succeeds and cases where it fails, but the learning effect of learning even those things also works. It is a technological innovation that has a high possibility of making a leap forward by linking with AI technology. The more data that accumulates, the more accurate judgments can be conveyed, and this technology opens up great possibilities simply by linking to the data at the time of purchase. The RSI management table and the trading data management table are associated with each other by brand and date (database-related diagram (Fig. 91)) (not limited to this method, the issue is associated with the purchase date (or sale date) and the value of the technical index. By doing so, the evaluation index of the information processing system will increase dramatically, and what you can do, what you can give advice, and what you can evaluate will increase at once. The effects of each aspect of buying and selling can be seen in a little more detail as follows.

(Specific example of calculation of evaluation index of technical index value)
See the actual example of RSI in the text.

(Specific example 1)
In the case of trading data subject to aggregation by investor, when purchasing, purchasing while feeling overheated calls attention to technical indicators, advises early sale such as loss cut, and when holding, at the purchase timing with a high probability of success. In the case of purchase, it has the effect of making it possible to offer advice on additional purchases, compare with other stocks, and present options for stock replacement.

(Specific example 2)
In the case of trading data to be aggregated by investment target, if the index gradually overheats at the time of holding, advice on sale or partial sale, comparison data with other investment targets with cheaper indicators, and ranking data It can be expected to have effects such as display, and at the time of sale, it is possible to add a function such as watching the price movement after the sale with the information processing system and notifying that the overheating feeling of the technical index has subsided.

(Significance of calculation of evaluation index of corporate performance)
Corporate performance can be said to be information that is inherent to stocks, and stock information almost always contains trends in corporate performance. However, this information is enormous and difficult to manage. It is often used as a basis for deciding what to buy at the time of purchase.

(Problems of conventional technology)
In terms of corporate performance, for example, a company that has a better performance than the expected number attracts attention and is bought. The reverse is also true. It is also common practice to buy and sell based on such information. However, if you use it to manage the stocks you own, the usage will change drastically. This is possible by linking it with purchase data. Normal corporate performance is provided as one of the stock information. Even if it is listed in the stock information, it is linked to the stock information. Even in the same corporate performance association, the date and the issue are associated with each other, and the issue is associated with the issue and displayed. Corporate performance is often displayed in association with this stock. In addition to stock charts, you can also see corporate performance on the management screen. Information linked to a brand, these are conventional technologies, and the issues of these conventional technologies must be managed by each person even if corporate performance etc. are posted, so for very ordinary people , There is a point that it cannot be managed. Just because the company performance is displayed together with the stocks held on the management screen, even if there is information, it is not tied to the purchase of oneself, so it is not personalized. However, if it is linked to the purchase date or sale date, it can be used for advice and diagnosis based on the timing of the purchase or sale, and it can be expected to have a very large effect that it can be used for comparison, ranking, evaluation, etc. It works, functions, and works completely differently from what is associated with a purchase or sale. What kind of effect will be produced if the database is linked to the purchase date, the brand code, and the corporate performance of the brand code?

(Action of calculation of evaluation index of corporate performance)
First, prepare another table. It is a table that includes at least one of the date, brand code, and corporate performance in the corporate performance table, and the corporate performance includes sales forecast value, sales performance, operating profit forecast value, operating profit performance value, etc. Ideally, it should be possible to manage the results on a yearly or quarterly basis (the table below the evaluation index calculation table (Fig. 111) is an example). For example, in the case of quarterly settlement, the first quarter is 10 billion yen, and if this is the actual value, this data and the date are linked and managed as the sales amount of the latest quarterly settlement. As of May 1, it was 10 billion yen, of which the actual value for the second quarter will come out. If the sales in the second quarter reached 12 billion yen on August 1, the sales amount of the latest quarterly settlement will be updated.

As a result, if the purchase date is 5/1, the latest quarterly settlement figures can be captured by the information processing system on 8/1. In other words, purchase data and corporate performance data are linked, and it is one of the important evaluation indexes for measuring investment results. Trends in corporate performance also have a large impact on stock prices and are a matter to be managed, but for busy investors, it becomes difficult to manage, and before you know it, you notice that the situation has changed due to poor performance. I usually do it without it. By linking this information, changes in corporate performance from the date of purchase will be linked to the purchase data and updated as needed. If there is an announcement of the earnings forecast after purchasing on 5/1, information such as the date and revision range will be managed, and if the revision of the earnings forecast that makes the difference between the forecast number and the actual value clear is announced, The date, correction range, etc. will be managed by the information processing system. This has a big meaning, and it has an important meaning, not just an announcement of common corporate performance.

(Effect of calculation of evaluation index of corporate performance)
One of the important meanings is the effect of being able to accurately catch changes in corporate performance from the time of purchase to the time of sale. Normally, such changes cannot be made without constant watching. However, by leaving this watch to the information processing system, it will be possible to determine which of the many stocks to watch out for and which stocks do not need to be closely watched now. Also, what is important is that corporate performance and trading data are related as one of the evaluation indicators. It is possible to verify various things such as which one has the higher profit / loss ratio. It is possible to compare both brands, and it is expected that advice and diagnostic ability will improve dramatically. For example, if the company's business performance is badly depressed or if the forecast figures change, what does the change mean? In the information processing system, create a table that defines rules such as such display. It has a special effect, such as being able to judge and display it. For example, if a downward revision of corporate performance is announced after a sale decision and the stock price drops significantly, the information processing system can read that the sale decision was correct and the sale was highly evaluated. It is possible, and these can be added to one of the evaluations as an example. As a feature of the top 10 stocks with the total profit / loss ratio in 2020, it is also possible to display together what kind of trend the corporate performance was, and which number should be used as a reference to see the evaluation index of the corporate performance. It can be expected to have the effect of making it possible to understand whether or not is important. Anyway, it is an invention that brings about unprecedented effects, to name a few.

(Specific example of calculation of evaluation index of corporate performance)
If you manage the corporate performance revision date and revision range, correction rate, sales, and operating profit, if you link this with trading data, it is best to purchase when the date has passed after the upward revision. Whether the winning rate is high or not can be calculated and displayed immediately by the information processing system.

(Specific example 1)
In the case of trading data subject to aggregation by investor, at the time of purchase, the future financial results announcement schedule of the relevant issue, PER at the time of purchase, dividend yield, etc. are automatically calculated and displayed or stored. At the time of possession, the information processing system can watch changes in corporate performance after purchase, and can manage notifications, change schedules and change dates, and change timings with the information processing system. In addition, at the time of sale, the stock price is sold from the selling price due to poor business performance, the stock price drops significantly, the technical index is judged to be cheap, and information such as comparison at the time of purchase is provided, and the correctness of the sale is evaluated. , It is expected to have effects such as being able to make a diagnosis.

(Specific example 2)
In the case of trading data to be aggregated by investment target, at the time of purchase, the company for the current term displays the forecasted sales and ordinary profit on the screen, and at the time of holding, when it changes sequentially, it tells the forecast number. You can see the transition of the product at a glance, and you can add a function to record the business forecast at that time at the time of sale and notify you when it is revised.

(Significance of calculation of evaluation index of trends of other investors)
In the case of trading data subject to aggregation by investor, it is extracted by "extraction condition: investor = investor A", but in reality, information of other investors such as investor B is also processed by the information processing system. , Accumulated. It is an excellent aspect of the information processing system database technology that it is easy to extract investors of the same brand and the same purchase date. In this case, the extraction condition is the trading data to be aggregated by investor. , "Extraction condition: Brand = relevant brand" AND "Purchase date = relevant purchase date", it is possible to extract trading data of the same brand and the same purchase date, and presenting that information is relevant. It can be easily done with an information processing system. From the trading data, it is also possible to display the sale date, the rate of holding, the trading data that is still held and the trading data that has already been traded in the opposite direction, and display the average value and the mode. Various things can be considered, such as calculating the value, the average rate of return of the trading data being bought and sold, and so on.

(Problems of conventional technology)
I want to check how I buy and sell the brand I bought, but until now there was no way. Not to mention the one action I bought on the same day. However, there is no more meaningful information for investors. I bought it on the same day, but it has plummeted. In fact, most of the people who bought on the same day are already sold out, but they are too busy to sell. You can see the situation. Of course, not everyone is right, and it is possible that the price will skyrocket after that, so it is not possible to decide whether it is good or bad, but at least it is very meaningful to be able to check the trends of other investors.

(Action of calculation of evaluation index of trends of other investors)
Under the above conditions, if extraction is performed with "extraction condition: brand = relevant brand" AND "purchase date = relevant purchase date", it is easy for the information processing system to extract trading data of the same brand and the same purchase date. Can be done. If various evaluation indexes are calculated for this trading data set by a procedure similar to normal trading data, the evaluation indexes derived from the trading data set of the purchaser of the same brand and the same purchase date are calculated. By using, you can easily compare with others and display your own ranking.

(Effect of calculation of evaluation index of trends of other investors)
The trends of other investors can be limited to the stock, the purchase date, the holding period of the stock, the sale date of the stock, and various other uses.

(Specific example 1)
In the case of trading data subject to aggregation by investor, what kind of investment type did other investors purchase at the time of purchase, what was the average purchase unit price, and what was the reference for the purchase? With the information processing system, you can grasp information such as whether people of the type purchased it, and when you own it, you can feel that the number of people who sell it gradually increases and the ownership ratio is decreasing. The information processing system also makes it possible to check how a group of people who buy and sell well works. At the time of sale, you can check whether your profit was set earlier or later than other people, whether the profit margin is higher or lower than the average, when the highest person sold, etc. Even after that, in the end, it is possible to expect the effect of being able to confirm how much the result of the brand was, etc.

(Specific example 2)
In the case of trading data subject to aggregation by investment target, at the time of purchase, it is possible to know how many participants are in total and what percentage of the total trading value is processed by the information processing system. , How many investors are selling today, what is the holding ratio, the ratio of the current holder and the profit / loss determinant at the time of sale, the average trading profit / loss ratio, the winning rate, etc. It is output and displayed as the data extracted only by the relevant purchase date of the brand.

(Significance of calculation of evaluation index of trends of other investment targets)
In the case of aggregated trading data by investment target, it is extracted by "extraction condition: investment target = investment target A", but in reality, information on other investment targets such as investment target B is also processed by the information processing system. , Accumulated. Extracting other investment targets purchased on the same purchase date is one of the excellent aspects of the database technology of the information processing system. In this case, the extraction condition is the aggregated trading data by investment target, and if the extraction is performed with "extraction condition: purchase date = relevant purchase date", the trading data on the same purchase date can be extracted and the information is presented. This can be easily done with the information processing system. From the trading data, it is also possible to display the sale date, the rate of holding, the trading data that is still held and the trading data that has already been traded in the opposite direction, and display the average value and the mode. Various things can be considered, such as calculating the value, the average rate of return of the trading data being bought and sold, and so on.

(Problems of conventional technology)
I want to check how I buy and sell the brand I bought, but until now there was no way. Moreover, we do not know the buying and selling behavior of other investment targets of investors who purchased on the same day. However, there is no more meaningful information for investors. I bought it on the same day, but the brand has plummeted. However, it can be seen that those who have purchased other brands are steadily increasing their unrealized gains. Of course, not everyone is right, and there is a possibility that it will plummet after that, so it is not possible to decide whether it is good or bad, but at least it is very meaningful to be able to check the trends of other investment targets.

(Action of calculation of evaluation index of trends of other investment targets)
Under the above conditions, if extraction is performed with "extraction condition: purchase date = relevant purchase date", it is possible to easily extract trading data of purchases of other investment targets on the same purchase date in the information processing system. If various evaluation indexes are calculated for this trading data set by a procedure similar to normal trading data, the evaluation indexes derived from the trading data sets of other investment targets of the purchaser on the same purchase date are calculated. , By using it, you can easily display the comparison with others, your ranking, etc.

(Effect of calculation of evaluation index of trends of other investment targets)
Trends of other investment targets can be limited to the purchase date, the holding period of the stock, the sale date of the stock, and various other uses.

(Specific example 1)
In the case of trading data subject to aggregation by investor, information such as how many shares were purchased for other investment targets at the time of purchase, how the participants of the investment target are compared to other investment targets, etc. However, with the information processing system, you can grasp it, and at the time of holding, the number of people who sell other investment targets gradually increases, and the ownership ratio is decreasing, but you can experience that the investment target has a high yield. The information processing system makes it possible to check what kind of stocks the group of people who buy and sell well purchased at the same time. At the time of sale, the profit taking of the stock was faster or slower than other investment targets, whether the profit margin was higher or lower than the average, and the highest person sold what investment target and the result. It is possible to confirm whether or not the price has increased, and even after the sale, it is possible to confirm how much the performance of the stock concerned was compared to other stocks, etc. ..

(Specific example 2)
In the case of trading data to be aggregated by investment target, whether there are more or less participants than other investment targets at the time of purchase, what is the ratio to the trading value, and the buying and selling of other investment targets at the time of holding. What is the difference in the winning rate, average holding period, winning profit rate, etc. of the investment target compared to the trend, and at the time of sale, how is the rate of increase / decrease during the holding period of this stock compared to other stocks? You can see if it was there, how the ranking was, and so on.

(Significance of evaluation index calculation table)
Creating a calculation table for evaluation indicators makes management easier, displays a list, makes instructions in the information processing system clear, and makes the definition clear. The evaluation indexes included in this evaluation index are limited to the evaluation indexes that satisfy the following conditions. It is an evaluation index that affects the investment profit / loss of the target, and it is a management item in the first step to the fourth step, or it is an item in another table linked to the trading data. The evaluation index used as a condition is an evaluation index that can be managed in the calculation table.

(Problems of conventional technology)
In the first embodiment of the prior art, the formula is displayed, but there is no concept of this calculation table. By creating a table, it can be centrally managed, the number of evaluation indexes can be increased, it is easy to manage, the instructions in the information processing system become clear, and it is easy to automate.
(Action of evaluation index calculation table)
As illustrated in FIG. 111 of the evaluation index, for example, the evaluation index called total trading profit / loss is an evaluation index calculated from the trading data at the trading profit / loss level, and is calculated as the total value of the trading data. Profit / loss level Calculated from trading data, but calculated from individual trading data, not total value, calculated from trading profit / loss and purchase amount by showing formula, average trading profit / loss ratio calculated individually from trading data Calculate the average of. This year's sales forecast will be incorporated into trading data using the performance forecast table, date, brand code, etc., and the transition of the sales forecast after the purchase date will be captured. By creating such an evaluation index calculation table, it is possible to determine the calculation method of various evaluation indexes and centrally manage them.

(Effect of evaluation index calculation table)
By accurately defining the calculation method of the evaluation index, if the evaluation index is determined, it is always calculated by the same calculation method. On the contrary, since the calculation method is determined here, it is possible to calculate the evaluation index from the trading data of any complicated extraction conditions. By deciding the calculation method in the information processing system, the definition of the evaluation index will be clarified, the background of the calculation of the evaluation index will be clarified, and the effect on profit and loss will be easy to understand. effective. For example, if the figures in the earnings forecast continue to increase, it will have a positive effect on investment profit and loss, and if downward revisions occur one after another, it will have an adverse effect. Of course, it is difficult to say unconditionally about stocks, but the good thing about table management is that the factors that affect investment profit and loss can be gradually increased.

(Specific example of evaluation index calculation table)
There is an example as shown in FIG. 111, but the present invention is not limited to this.

(Significance of calculation of evaluation index of trading data subject to aggregation by investment target)
The trading data to be aggregated by investment target is the trading data created by the information processing system in the second step, and the profit / loss level trading data is created from the trading data by the information processing system (in any order). The calculation of the evaluation index from the trading data is defined as the calculation of the evaluation index of the trading data to be aggregated by investment target.

(Technical issues)
For example, what kind of trading is being done for S1 company stock and S2 company stock, and what is the average stock price of investors currently holding, and what is the average buying and selling? The people who have done so have not known what kind of buying and selling they have done. The idea of changing the trading data managed for each investor into trading data managed for each investment target, the idea of converting the trading data into profit / loss level trading data, and the trading profit / loss calculated from the trading data set. It is an evaluation index that goes through the process of calculating an evaluation index that has an influence on the data in the information processing system, and is an evaluation index that can be derived for the first time. It is a technique that can be done for the first time with the linked information processing system to calculate the evaluation index, and if you stumble somewhere, a number far from the target evaluation index will come out. The solution to this problem that investors really need is the calculation of the evaluation index of the trading data to be aggregated by investment target.

(Action of calculation of evaluation index of trading data subject to aggregation by investment target)
As described above, the information processing system can create a ready-to-use trading data set from which important evaluation indexes can be calculated for the first time through the steps of the second step to the fourth step. To show the process of implementation, the target is determined by setting the trading data to "extraction condition: brand code = 9984", profit / loss level trading data is created based on the trading data, and the evaluation index is calculated from the trading data. do. The evaluation index of the investment target is determined by determining the target target, the target profit and loss, and the evaluation index. Another feature is that since this evaluation index is linked not only with transaction data but also with market data, corporate performance data, etc., and transaction data, the purchase data of S company stock is linked with corporate performance and charts. The effect is outstanding. The trading data set is the trading data created to capture the trading trends of the previous Softbank shares, and was created through a process specially performed by the information processing system in order to increase the trading profits and losses of the Softbank shares. It is a trading data set. The evaluation index calculated from the information processing system can generate a large number of evaluation indexes according to this purpose by the information processing system.

In the trading data to be aggregated by investment target, the extracted trading data to be aggregated by investment target under "Extraction condition: Investment target = A issue" is the total profit / loss level trading data, the second level trading data and the third level trading data. , 4th level trading data is created by the information processing system. Furthermore, for each trading data, necessary evaluation indexes such as winning / losing, profit / loss ratio, elapsed days, turnover days, unrealized profit / loss ratio, total profit / loss ratio, etc. are calculated by the information processing system using various profit / loss level trading data. ,Remember. If you do this in cooperation with a computer, today's numbers will come out in a blink of an eye, and tomorrow, different numbers will come out, and if you buy or sell, they will be fixed and change in a complicated way. It is a technique that can be linked with this database that can be updated while changing the situation every day, and its significance is great. It is a technology with dramatically expanded possibilities. In this case as well, instructions are issued and executed according to consistent rules from the acquisition of trading data to the calculation of evaluation indexes, and various evaluation indexes that are factors that move the target profit and loss can be calculated, and the calculated evaluation indexes can be used. In particular, the technology has advanced in that the actual operation (display of evaluation index, display of advice, etc.) is maintained consistently by using it. Because of this consistency, it is possible to have more management items in the trading data, and it is technically significant that various information in the form linked to the trading data can be used for the calculation of the evaluation index. .. For example, it is a typical example (see Fig. 105 etc.) that the purchase date and the trading data of other stocks purchased at the same time linked to the stock code are linked, and it has never been realized until now. .. As a result, it is a technological innovation that dramatically improves the ability to give advice to investors, diagnostic ability, and understanding of investment targets.

(Effect of calculation of evaluation index of trading data subject to aggregation by investment target)
This effect is enormous, and it is an invention with sufficient social impact. Not only stocks such as S1 company stocks, but also how stocks are bought and sold, investors can understand whether they are winning or losing, and holders and traders (frequently buy and sell) Which of the investors) is making a profit, how much profit is generated by holding, how it is made, how the loser is losing, etc. There is an impact that the actual situation of is clarified.

Furthermore, linking transaction data with investment target charts, technical indicators, and corporate performance information has great significance, and is a technology that creates various technological innovations. The realization of this technology is created by the cooperation of databases, which is the division of roles by the information processing system. For example, FIGS. 103 to 106 have great meaning, such as the contents produced by this technological innovation. In the first embodiment, the calculation of the evaluation index related to the trading data was mainly performed, but in the fourth embodiment of the information processing system, the trading data can have more items, for example, the purchase date and the brand. The information associated with the code alone includes technical index values, corporate performance, investment behavior of other investors of the stock, and the actual purchase of other stocks on the same day. This is information that cannot be managed very much unless it is a database linkage technology, and can be realized only in the fourth embodiment. The fact that such information and trading data can be linked and linked changes with what other investors are doing depending on the trends in corporate performance and technical index values after purchase, and if it is another stock. In addition to knowing whether to proceed, it will be possible to change advice, change diagnosis, and refer to the sale and holding status of people of the same brand and the same purchase date of different investors. It has immeasurable effects such as being able to do it. Even with the same advice to investors, the main reason why the fourth embodiment has evolved incomparably with the first embodiment is this database linkage. In addition, it has become possible to dig deeper into investment targets, and it is very significant that it is linked to actual investment behavior that cannot be understood from technical indicators or corporate performance.

(Specific example of calculation of evaluation index of trading data subject to aggregation by investment target)
In addition to the examples given above, many examples are described herein.

(Definition of calculation of evaluation index based on trading data, which is a component of trading data to be aggregated by investment target)
Going one step further from the above calculation based on the aggregated trading data by investment target, the items (components) managed by the aggregated trading data by investment target include the process of extracting, classifying, and tabulating by the relevant information processing system. This is defined as the calculation of the evaluation index based on the component trading data of the trading data to be aggregated by investment target.

(Problems of conventional technology)
For example, the investment performance ranking by investor of S1 company stock, the investment performance ranking by stock brand, and the investment performance cannot be grasped by the calculation of the evaluation index of the above-mentioned aggregated trading data by investment target. Comparison of S2 company stocks is a further managed item (component), and the necessary evaluation index cannot be calculated unless the process of extraction, classification, and aggregation by the information processing system is included. In some cases, the same purpose can be achieved even if the extraction conditions are increased in the process of creating the trading data to be aggregated. For example, if S1 company stock and A investor are set as extraction conditions, the trading data of Mr. A's S1 company stock will be obtained. It is a data set that is easy to compare with trading data side by side and to process when ranking. Furthermore, if the number of management items is increased, various types of evaluation indexes can be calculated.

(Components of trading data to be aggregated by investment target Calculation of evaluation index based on trading data)
Various evaluation indexes are calculated by the information processing system for the trading data set created through the steps of creating trading data to be aggregated by investment target, the step of creating component trading data, and the step of creating profit / loss level trading data. do.

(Effect of calculation of evaluation index based on trading data, which is a component of trading data to be aggregated by investment target)
Investing in investment targets from various perspectives, more than calculating the evaluation index of trading data to be aggregated by investment target. There is an effect that can be clarified. In addition to the previous example of S1 company stocks, for example, it is possible to compare and rank the investment behavior of stocks, virtual currency, and FX in detail by winning rate and return on investment. It is an invention that gives various impacts.

(Specific example of calculation of evaluation index based on trading data, which is a component of trading data to be aggregated by investment target)
Again, many examples are given in this specification.

(Specific example 1 (repost))
In the case of trading data to be aggregated by investment target, whether there are more or less participants than other investment targets at the time of purchase, what is the ratio to the trading value, and the buying and selling of other investment targets at the time of holding. What is the difference in the winning rate, average holding period, winning profit rate, etc. of the investment target compared to the trend, and at the time of sale, how is the rate of increase / decrease during the holding period of this stock compared to other stocks? You can see if it was there, how the ranking was, and so on.

(Components of trading data to be aggregated by investment target (investor) Definition of calculation of evaluation index based on trading data)
For example, stock information includes innumerable information on price movements such as charts and technical indicators, but actual investment behavior is veiled. Investor investment behavior is always behind the rise in the chart. In order to grasp the investment behavior of this investor, the process of extracting, classifying, and tabulating by the information processing system is performed based on the investor managed by the information processing system in the trading data to be aggregated by investment target. It is defined as the calculation of the evaluation index based on the investor-specific trading data of the investor-specific aggregation target trading data.

(Problems of conventional technology)
Taking the example of S1 company stock, it is completely unknown how institutional investors, foreign investors, margin trading and physical trading are trading, and what is the current holding status. It is significant that such information is released to the world.

(Components of trading data to be aggregated by investment target (investors) Effect of calculation of evaluation index based on trading data)
Based on the trading data to be aggregated by investment target created in the second step, the trading data extracted, classified and aggregated by investor, and the trading data created by taking the step of creating profit / loss level trading data Based on this, various evaluation indexes are calculated by the information processing system.

(Components of trading data to be aggregated by investment target (investors) Effect of calculation of evaluation index based on trading data)
The evaluation index calculated in the process by the information processing system can be expected to have a special effect of clarifying the investor behavior for the investment target. For example, the speculative behavior of a trader's stock creates a situation where it is not known who buys and sells and how. Information that agitates investors' anxieties and feelings and incites buying and selling is incessantly distributed by methods such as Twitter and bulletin boards. It is significant to understand what kind of situation the people who are buying stocks with speculative movements are in, which is the number of winners and losers, and what kind of behavior is being done, and it is important to invest. It has a big impact on behavior. It is the effect of this invention that the loss of society due to speculative behavior is also clarified.

(Components of trading data to be aggregated by investment target (investor) Specific example of calculation of evaluation index based on trading data)
Specific examples are also given in various parts of the specification.

(Definition of calculation of evaluation index based on trading data by investment target (investment target))
Information on investment products such as stocks, FX, and virtual currencies is innumerable, and information on price movements such as charts and technical indicators is available, but actual investment behavior is wrapped in a veil. Behind the rise in the chart is always the investment behavior of investors, and that behavior varies from stock to stock. It is very meaningful for those who have never invested to understand how the investment behavior of each stock is different among many stocks.

(Problems of conventional technology)
Among the stocks, there are stocks in which dangerous speculative behavior is noticeable, and stocks in which the price rises slowly over time and there is little fluctuation. These appear in charts and price movements, but are very difficult for general investors to understand. This is because the rising figures and numerical values look the same. This incomprehensible factor is a factor that keeps investment away, and is one factor that makes it impossible to clarify the difference between gambling and investment.

(Components of trading data to be aggregated by investment target (investment target) Effect of calculation of evaluation index based on trading data by investment target)
By calculating the evaluation index based on the trading data by component (investment target) of the trading data to be aggregated by investment target, it is possible to clarify the investment behavior of each stock that has been veiled up to now. .. The calculation process is as follows: Create aggregated trading data by investment target of the upper concept, extract, classify, and aggregate by investment target of the lower concept of the investment target, and collect profit / loss level trading data in the information system. It is possible to calculate the evaluation index based on the created and created non-equal trading data. The investment behavior of the target investment target is clarified.

(Effects of calculation of evaluation index based on trading data by investment target (investment target))
There is an effect such as clarifying the investment behavior of each stock (upper concept) by issue (lower concept).

(Specific example of calculation of evaluation index based on trading data by investment target (investment target)
When the investment behavior of each stock is clarified, the people who buy and sell the stock of company T are not profitable even though the Nikkei average is rising, or the whole is falling sharply. In September, it will be revealed that everyone is making a profit on this stock.

(Definition of calculation of evaluation index based on trading data subject to aggregation by investor)
The calculation of the evaluation index based on the trading data subject to aggregation by investor is the problem of what kind of evaluation index is calculated from the trading data of Mr. A. This is described in detail in the first embodiment, but it is the simplest and easiest to understand, which is used for diagnosing and giving advice on the trading data of Investor A. Investor A is an evaluation index that is necessary to understand how he has won, lost, and what the situation is now. There are many findings that can be obtained by calculating various evaluation axes and various evaluation indexes as in the first embodiment.

(Problems of conventional technology)
However, in the first embodiment, a lot of descriptions are devoted to the formula of the evaluation index, what kind of diagnosis can be made by the evaluation index that can be obtained there, and what kind of advice can be given. It has a technical problem that it is difficult to apply because it has not clarified a series of flow such as instruction of conditions such as acquisition to extraction, instruction of classification and aggregation processing rule, calculation of evaluation index that affects target profit and loss. ing. The information processing system is overwhelmingly technical in that it calculates the evaluation index by automatically giving instructions to the information processing system in cooperation with these, and further systematizes how to utilize it. It is a technology that is excellent in information processing, has good applications, and can solve many investment issues. There are many technical advantages compared to the first embodiment, but the two most important points will be touched upon here. As mentioned earlier, the factors that affect the investment profit and loss of investors through database linkage are, in the fourth embodiment, not only the trading data such as the winning rate, but also the evaluation of the trading timing and the change in corporate performance. In other words, by incorporating changes in fundamentals, behavior of the same stock of other investors, trends of other stocks on the same purchase date, etc. into the evaluation index of the information processing system, these evaluation indexes are used to improve investment profit and loss. It is significant that it has become possible to utilize it.

(Action of calculation of evaluation index based on trading data subject to aggregation by investor)
Based on the investor-specific aggregated trading data (created in the second step) extracted by "Extraction condition: Investor = Mr. A" in the investor-based aggregated trading data, the profit / loss level trading data of the fourth step is obtained. create. For the profit / loss level trading data, the first level (total profit / loss) trading data, the second level trading data, the third level trading data, and the fourth level trading data are created by the information processing system. Furthermore, for each trading data, necessary evaluation indexes such as win / loss, profit / loss ratio, elapsed days, turnover days, unrealized profit / loss ratio, and total profit / loss ratio are calculated by the information processing system based on various profit / loss level trading data. ,Remember. If you work together on a computer and do this, today's numbers will come out in a blink of an eye, and tomorrow's different numbers will come out, and if you buy or sell, they will be fixed and change in a complicated way. It is a technique that can be linked with this database to update them while changing the situation every day, and its meaning is great. This is a technology with much wider possibilities than the one that can be obtained by using a simple calculation formula as in the first embodiment. In this case as well, instructions are issued and executed according to consistent rules from the acquisition of trading data to the calculation of evaluation indexes, and various evaluation indexes that are factors that drive the target profit and loss can be calculated, and the calculated evaluation indexes can be calculated. In particular, the technology has advanced in that the consistency of the actual operation (display of evaluation index, display of advice, etc.) is maintained by using. Because of this consistency, it is possible to have more management items in the trading data, and it is technically significant that various information in the form linked to the trading data can be used for the calculation of the evaluation index. .. For example, it is a typical example that the purchase date and the trading data of an investor who purchased the same brand at the same time linked to the brand code are linked (see FIG. 105, etc.), and this is never realized in the first embodiment. It is impossible. As a result, it is a technological innovation that dramatically improves the ability to give advice to investors and the ability to diagnose.

(Effect of calculation of evaluation index based on trading data subject to aggregation by investor)
In the first embodiment, the calculation of the evaluation index related to the trading data was mainly performed, but in the fourth embodiment of the information processing system, the trading data can have more items, for example, the purchase date and the brand. The information associated with the code alone can include technical index values, corporate performance, the same stock of another investor, the same day's purchase, and so on. This is information that cannot be managed very much unless it is a database linkage technology, and can be realized only in the fourth embodiment. The fact that such information and trading data can be linked and linked changes advice depending on the trends in corporate performance and technical index values after purchase, the behavior of other investors on the same issue, and the trends of other issues on the same purchase date. In addition to being able to change the diagnosis and making it possible to change the diagnosis, there are immeasurable effects such as being able to refer to the sale and holding status of the same brand of another investor and people with the same purchase date. Even with the same advice to investors, the main reason why the fourth embodiment has evolved beyond comparison with the first embodiment is the database linkage by the information processing system.

(Specific example of calculation of evaluation index based on trading data subject to aggregation by investor)
In addition to the specific examples mentioned above, you can instruct the information processing system to watch the brand after sale and notify you when it reaches a certain technical index value, or your actual trading is confirmed and profits When the profit is confirmed, the storage unit 33 stores the trading profit / loss ratio among those who purchased the same brand on the same day, etc. every time the profit is confirmed, and issues a total generator. This makes it possible to provide advice and diagnosis that would not be possible at the time of the first embodiment.

(Specific example 1 (repost))
In the case of trading data subject to aggregation by investor, information such as how many shares were purchased for other investment targets at the time of purchase and how many participants of the investment target are compared to other investment targets is also the information information. With the system, you can grasp it, and at the time of holding, the number of people who sell other investment targets gradually increases, and the ownership ratio is decreasing, but you can experience that the investment target has a high yield and is good at it. It is also possible with the information processing system to confirm what kind of stocks the group of people who buy and sell in the same period purchased. At the time of sale, the profit taking of the stock was faster or slower than other investment targets, whether the profit margin was higher or lower than the average, and when and what kind of investment target was sold by the highest person. It is expected that it will be possible to confirm whether the results have been achieved, etc., and even after the sale, it will be possible to confirm how much the results of the stock concerned were compared to other stocks. can.

(Definition of calculation of evaluation index based on trading data by investor (investment target))
The trading data by component (investment target) of the trading data to be aggregated by investor is, in other words, the trading data of the stocks bought and sold by Investor A, and the evaluation index is calculated for each stock. Point to that.

(Problems of conventional technology)
Even if you unravel the account of investor A's securities company, it is very difficult to understand which brand has won and which brand has lost. All you can understand is that you can get an overview of the status of the stocks you own (portfolio browsing), and the trading status is particularly difficult to understand, and to understand it in an easy-to-understand manner, you can download the CSV and manage it yourself, which is very difficult.

(Components of trading data subject to aggregation by investor (investment target) Effect of calculation of evaluation index based on trading data)
By using the information processing system, this problem can be solved immediately. In the trading data to be aggregated by investor, the extraction condition is "Investor = Mr. A", the components are classified by brand, and the information system is instructed to create a trading data set without aggregation, and trading is performed. Profit / loss level Instruct the information system to create trading data, calculate various evaluation indexes for each trading data of the trading data set with the information system, and with this, the trading data of the stocks that investor A has bought and sold. Therefore, an evaluation index is calculated by the information processing system for each issue and each sale.

(Effects of calculation of evaluation index based on trading data by investor (investment target))
The evaluation index is an evaluation index derived in cooperation with a database, and can be used in various ways by itself. By calculating the average value for each issue with the information system, the information such as the investment amount per issue, the sale amount per issue, the profit / loss amount per issue, the average ROI, etc. for each issue of Mr. A. Calculated by the processing system, many important indicators that show the characteristics of investor A's buying and selling, how they are winning and how they are losing are derived. This is similar to the evaluation index of the first embodiment, but the information system is linked with a database, and various extraction conditions, aggregation rules, and classification criteria are clearly instructed to the information system to evaluate the purpose. This is an invention in which technology has greatly advanced in that an index can be calculated.

(Specific example of calculation of evaluation index based on trading data by investor (investment target))
Here, various evaluation indexes calculated by the information processing system may be displayed as they are, or may be moved to a comparison step and compared with a comparison target, or proceed to a ranking step with other investors. It is also good to use it for comparison, ranking of stocks bought and sold by Investor A, and a diagnostic result report using the evaluation index may be generated by the information processing system, based on those results. You may give some advice.

(Definition of calculation of evaluation index of trading data subject to aggregation by excellent investor group)
For example, the excellent investor group is defined as the top 30 overall profit / loss ratio for the last year. The calculation of various evaluation indexes of the excellent investor group is defined as the calculation of the evaluation index of the trading data to be aggregated by the excellent investor group.

(Problems of conventional technology)
In Forex etc., there are copy trades of excellent traders, but there are many stocks, many options, and it is difficult to invest in stocks with various investment forms. In addition, most copy trades themselves compete for short-term results, and even if they pass in a short period of time, they soon stop working. However, there is an excellent investor group that has achieved excellent results, and there should be many points to be learned from the trading data. It is not just a copy, but the profits that excellent investors can understand in such cases, what kind of buying and selling, what kind of brand they are buying and selling now, etc. are immeasurable.

(Action of calculation of evaluation index of trading data subject to aggregation by excellent investor group)
Create aggregated trading data for each investor for the most recent year, which is grasped by the information processing system. First level profit and loss level Create trading data and calculate the total profit and loss ratio. If you set up a program to update it every day, the top 30 investor groups in the total profit and loss ranking that will be updated every day will be decided. By calculating various evaluation indexes with the investor as the top 30 in the total profit / loss ratio ranking, it is possible to calculate the evaluation index of the trading data subject to aggregation by the excellent investor group.

(Effect of calculation of evaluation index of trading data subject to aggregation by excellent investor group)
Having a group of excellent investors for the year, which is updated daily, is significant not only for short-term success, but also for the buying and selling of successful groups of investors throughout the year. For example, on a chart as shown in FIGS. 103 to 106, it is possible to display the top 10 stocks handled by the excellent investor group during the holding period of the stock, the top 10 stocks purchased on the purchase date, and the like. In addition, if you are an excellent investor group, you can check the history of how the stock was bought and sold, including other periods. By referring to these, it is significant to see the direction of how to improve.

(Specific example of calculation of evaluation index of trading data subject to aggregation by excellent investor group)
In addition to the top 30 total profit / loss ratios for the last year mentioned above, the top 20 total profit / loss ratios for the same investment type for the last year, the top 10 trading profit / loss ratios, or temporary in the past. Instead of the investors who are ranked high in the ranking, you may always classify them as the top ranking regular group that is always ranked high, and the excellent investor group can be classified according to various criteria. It is possible. As long as the classification is possible, the evaluation indexes can be calculated by following the same procedure, and those evaluation indexes can be used as excellent investor group evaluation indexes for comparison, and also for the evaluation of the investor. It can be used, and it can also be used for diagnosis and advice. Of course, as an article, it is possible to provide article data such as "What is the secret to the success of the top 10 excellent grades in Corona?"

(Significance of calculation of evaluation index of trading data subject to average investor group aggregation)
It would be useful to know the average figure of all investors, not just the best investors.

(Problems of conventional technology)
The average figure of all investors is unclear until now. Investors have been buying and selling over the past year and the average has risen, but we don't know what the actual investment outcomes were. Even this average figure is currently a black bock. With this, I could not see a sense of direction such as how to move in a better direction, and I ended up investing in the dark clouds, and some investors such as bulletin boards and Twitter took action. It will be lost.

(Action of calculation of evaluation index of trading data subject to average investor group aggregation)
With the information processing system, at a minimum, by updating the necessary indicators such as the total profit / loss ratio for the last year, the last month, the last three years, etc. for each investor every day, the average value etc. can be immediately obtained. Can be calculated. The important thing is to decide and routineize the data that is updated daily for each investor based on what criteria (for example, the last year) and which evaluation index (total profit / loss ratio, etc.) should be updated. As a result, in the information processing system, it is not easy to obtain an average value. The same applies to the average value of investor groups.

(Effect of calculation of evaluation index of trading data subject to average investor group aggregation)
Some investors are medium- to long-term investors, while others are good at short-term trading. First of all, it will be possible to compare what your position is with respect to the average, what is inferior, what is superior, and so on. Even if the appearance of excellent investors appears in magazines, the average appearance does not easily emerge. As a result, the merit of knowing the average image is a basic figure, whether it is a comparison target or a diagnosis of what is superior or inferior to the average, and it is an investment that has been a black box until now. It brings immeasurable benefits to the whole picture of the house.

(Specific example of calculation of evaluation index of trading data subject to average investor group aggregation)
The average image of short-term trading type, the average image of medium- to long-term investors, and the average image of shareholder benefit investors can be mentioned.

(Definition of calculation of evaluation index based on trading data subject to aggregation by period)
There are four types of trading data to be aggregated by period, and only the completed version can correctly capture the evaluation index. The fact that the liver of the completed version is a revaluation is described in detail in the column of creating trading data subject to aggregation by period. It is significant to be able to grasp the evaluation index for each period. In general, in the transition of a certain valuation amount, it is common to use the rate of increase / decrease of the valuation amount, to visually show the valuation amount in a chart, or to show the valuation amount at a certain point in a separate screen as a detailed screen. Is.

(Conventional technical issues)
As mentioned in the section on trading data subject to aggregation by period, in order to report the investment results in 2020, you can accurately grasp the dynamically changing trading data by continuing to hold or buying and selling. It's difficult without it. Of course, the figures for the entire valuation are easy to grasp, but it is very difficult to understand because the maze is beyond that. Therefore, the current situation is that the period comparison of securities companies is about the change in the valuation amount. However, as a precaution, there are cases where an approximate value is obtained even if another method (similar form 1 or the like (see trading data subject to aggregation by period)) is used. This is a case where day traders and the like frequently buy and sell. If you are a day trader, you do not have to take holding into consideration (since only those bought and sold during the period, an approximate value will be obtained). Therefore, the profit / loss by period will be a near figure even in the similar form 1. It's not accurate, but it's okay because there isn't enough error to make a mistake. However, the more macro numbers there are general investors and various investors, the farther they are from the actual situation. Usually, investment products are meaningless unless you can see the trading data including those who buy and sell frequently and those who keep holding them. However, if this is grasped by period in the information processing system, the number of things that can be understood will increase dramatically, and the number of evaluation indexes will be different.

(Action of calculation of evaluation index based on trading data subject to aggregation by period)
Taking the case of grasping the trading status of Mr. A in 2020 from the trading data (completed version) subject to aggregation by period, January 1, 2020 is set to time A, and December 31, 2020 is set to time B. Then, starting from the trading data at the time B, an instruction for revaluation is issued to the information processing system. By setting "Extraction condition: Investor = Mr. A", issuing an instruction to create the trading data with the trading profit / loss level trading data, and issuing an instruction to calculate various evaluation indexes from the trading data set to the information processing system. The evaluation index is calculated. This is the calculation of the evaluation index based on the trading data subject to aggregation by period in the simplest case, but the more conditions are added, the more complicated the condition setting becomes, and the principle does not change. With this, Mr. A's average return on investment in 2020 and Mr. A, an investor in 2020, have made various purchases and sales, but in the end, was the result of 2020 a loss or a profit? If there is a profit, how much is that amount, what is the average return (ROI) for the purchase amount (investment amount), how often is it bought and sold, and the average number of days held. Depending on the information processing system, various evaluation indicators such as how much, how was the win rate, and on average, when the technical index value was decided to buy and sell. , Will be guided. If we limit the period of 2020, even such a simple number will not come out properly. Even if it appears, it is due to another method (similar form 1 or the like) in the trading data subject to aggregation by period. This is because if you buy and sell frequently such as day traders, you do not have to take holding into consideration (since only those bought and sold during the period, an approximate value will be obtained), so the profit and loss by period is a near number. It's okay because it comes out, but the more macro numbers there are general investors and various investors, the farther away from the actual situation. However, if this is grasped by period in the information processing system, the number of things that can be understood will increase dramatically, and the number of evaluation indexes will be different.

(Effect of calculation of evaluation index based on trading data subject to aggregation by period)
It is possible to calculate an evaluation index that is incomparable to the fact that the evaluation value transition of the previous securities company example can only be shown in chronological order, and by doing so, evaluation, advice, diagnosis, etc. to investors can be dramatically improved. improves. All of them are the result of technological innovation that started from the revaluation of the trading data (complete version) subject to aggregation by period. In the pseudo form 1, if the purchase date is set to January 1, 2020 or later and the sale date is set to December 31, 2020, a pseudo value may be obtained. If it is a trader's evaluation, this may be sufficient in some cases. However, in reality, it is not a number that represents an accurate period profit or loss. Simply put, I bought it in December 2020 and kept it until January 2021, but the stock had tripled. Such cases are completely leaked. There are many leaks like this, so even if you use them, you cannot evaluate them correctly. It may be enough for individual investors to see the results of their traders, but in a world with a variety of investors, it's a very unacceptable view. On the other hand, after performing correct revaluation with the period-specific aggregation target trading data (complete version) by the information system, all the evaluation indexes calculated through the subsequent steps such as profit / loss level trading data are accurate numbers. Therefore, the correct period investment profit / loss and the correct evaluation index can be calculated by the information system. This is very important that affects the evaluation, ranking, comparison, diagnosis, advice, etc. that are the subsequent processes, and the wrong number will be the wrong number no matter how far you go, and the evaluation will also be wrong. And the advice will be wrong. For example, in the previous example, even though we had tripled stocks, they were not evaluated at all, and the evaluation was that the period was considerably inferior to the average. The process is very important.

(Specific example of calculation of evaluation index based on trading data subject to aggregation by period)
This specification gives a lot of concrete examples of the evaluation index based on the trading data subject to aggregation by period, but "This is the top 10 stocks with the trading profit / loss ratio in August!", "The investment results in 2020 are high. Article data such as "Which is it? Day trader vs. medium- to long-term investor" can be created immediately with the information processing system. There are many other possible approaches.

There are three methods for calculating the evaluation index (such as trading data by profit / loss level stage). Of the evaluation indexes calculated by the information processing system from this step, which evaluation index is important and which evaluation index is important. There may be a judgment step as to whether or not the value is low. But it's not essential. This is because the trading data has been narrowed down considerably up to the fourth step, and a huge number of evaluation indexes are not produced, and it is easy to judge the importance to some extent.

(Definition of evaluation index selection judgment process)
With only the total profit / loss level evaluation index, some evaluation indexes are calculated by the information processing system. These are evaluation indexes calculated by the information processing system from trading data (trading data in a narrow sense = transaction data). For example, rights data, corporate performance data, investment type data, and technical data, which are trading data in a broad sense. Index values and the like are also included in the trading data created up to the fourth step as necessary, and are calculated from these by the information processing system. For example, it is possible to calculate an evaluation index such as an evaluation index calculated from corporate performance data and an evaluation index calculated from right data associated with a brand, purchase date, etc. from split right data. However, this process is the step of selecting which evaluation index is important and which evaluation index is useful for improving the target profit and loss. It does not mean that the evaluation indicators should be expanded, but the evaluation indicators necessary for improving profit and loss have already been narrowed down (in the process from the second step to the fifth step), and on top of that, the importance is even higher. It is the process that determines the evaluation index.

(Issues in the process of determining the selection of evaluation indicators)
In the first embodiment, many actual examples are shown regarding the calculation of the evaluation index and the evaluation index used for advice, diagnosis, and the like. Which of the many evaluation indicators is important, this evaluation index for Mr. A, this evaluation index for Mr. B, and this evaluation index for stock A are the most important evaluation indexes that have a large effect on profit and loss. It is easier to use and understand if you answer that there is. In the fourth embodiment, it is reported that the profit / loss level evaluation index is calculated by the information processing system by three methods. It is a step to make the selection in the same way, but there are some expressions that are a little difficult to understand, so here I will explain the process of selecting the evaluation index again.

(Action of evaluation index selection judgment process)
The process of determining the selection of this evaluation index will be described with reference to FIG. 78. Regarding the evaluation index importance judgment step (J101), first, the information processing system instructed to create a comparison table V3 with the average of the evaluation indexes in order to know what the evaluation indexes are important for comparison for Mr. A. (J102). By creating a comparison table of evaluation indexes that includes the deviation rate from the average, the evaluation index that deviates from the average is specified (U101). Then, in order to know what is the important evaluation index among the many calculated evaluation indexes, the weighting of each evaluation index is changed by the evaluation index weighting rule (J103). The evaluation index having a high deviation rate in U101 is weighted more, and the profit / loss at the higher profit / loss level is weighted more, so that the weighting of the evaluation index and the profit / loss level deviating from the average is changed (U102). Specifically, the information processing system refers to a table such as V2 to increase the score of each evaluation index, and the weighting is executed (U102). The results of the weighting performed are quantified and sorted in order of importance (J104), (U103), etc. to determine the order of which evaluation index is particularly important.

In the evaluation index calculation table (V1) of FIG. 80, the target trading data (extraction conditions, etc.) is determined up to the fourth step, and the target profit / loss is determined, so that the evaluation index that can be calculated by the information processing system is determined.

(V1-1) Of the many evaluation indexes in the evaluation index calculation table of V1 in the weighting table (V2) of the profit / loss level and the weighting table (V3) of the deviation rate from the average value, which evaluation index is the most important evaluation index (V1-1). KPI) will be decided.

Explaining (V2), the first-level total profit / loss includes both trading data that has been bought and sold and trading data that is not opposed to trading, which is just a comprehensive index, and the weighting is set to the highest (table). In a specific example, 5). At the second level, the trading profit / loss level is the confirmed trading data, and the unrealized profit / loss level is the data currently held by unopposed trading, so the score is one step lower than the total profit / loss level. However, since the unrealized gain / loss is the data currently held and the trading profit / loss is the past trading, there are cases where it is better to increase the weighting of the current holding. The example of the score is just an example, and it is decided by trial and error.

Next, regarding V2, the case of investor A and the case of investment target A issue are different, so they will be described separately. In the case of Investor A, there are various comparison targets such as the average of all investors and the average of investment type A, but the explanation will be given using the basic comparison with all investors. When comparing the evaluation index of investor A with the evaluation index of the average, Mr. A shows how much the evaluation index deviates from the average. However, it should be noted here that there are evaluation indicators that have a positive effect on profit and loss and evaluation indicators that have a negative effect on profit and loss because it is for improving profit and loss. However, in the latter case, the higher the negative divergence rate, the higher the result of Mr. A, so it is necessary to match the score accordingly. It is represented by plus and minus in the correlation index item.

In the case of investment targets, the evaluation index calculated by the information processing system from the transaction data (such as the trading profit / loss ratio) is important, but the evaluation index calculated by the information processing system from the market data also becomes more important. This is because it contains a lot of data that greatly affects the profit and loss of the investment target. For example, if there is a stock that has announced that its corporate performance is much higher than expected, there are cases where the unrealized profit margin of the holder is expected to increase and the overall profit and loss is expected to increase. In this case, it is necessary to include this evaluation index in the evaluation index of issue A and show that this evaluation index is important as a KPI. This point of view is especially important for trading data created from trading data by investment target.

For example, when creating the trading data to be aggregated by investment target of issue A, if it is imported in the upward revision table as described above, the date of upward revision and the upward revision rate, etc. are linked to the issue and become issue A. Is also tied. If there was an upward revision yesterday, that date and the upward revision rate will be one of the data items of the aggregated trading data by investment target of issue A, and from there, the profit / loss level trading data calculated by the information processing system will be used. However, the item exists, and the information processing system of the evaluation index allows the upward revision rate of issue A to be used as the evaluation index and to follow the evaluation index calculation table. If the upward revision rate is high, the importance to the stock will be very high, and if the weighting is also large, the KPI of the A stock will be the most important upward revision rate, the second is the unrealized profit rate, the third is the technical indicator RSI, etc. Will be.

All the items managed in the first step of the trading data acquisition step and the second step of creating the trading data to be aggregated can be included in the calculation step by the information processing system of this evaluation index. The score of the upwardly revised stock is set to be higher as the date is most recent, and the score is higher as the upwardly revised rate is higher, which is set in the weighting table of other evaluation indexes of V5.

If such weighting is performed, the diagnosis result, which is the subsequent process, states, "Because the upward revision rate announced after the purchase date was very high, the unrealized profit margin is now 30%. It is getting higher and raising the overall investment profit and loss. " It is a diagnosis that can be made and advice because everything is related. With KPIs, it is possible to emphasize and convey even more.

Of course, there are positive and negative correlations as in V3, and there may be cases where it is better to compare with the average, and stocks that have been announced and stocks that have not been announced, such as upward revisions. Here, the trading data created from the aggregated trading data by investment target and investor has been described, but the same can be done for the aggregated trading data by period, other aggregated trading data, component trading data, and the like. In the case of trading data subject to aggregation by period, a little supplement is added. Comparing the 2020 evaluation index with the average, which evaluation index was more important in 2020 compared to the 10-year average for all investors is determined in the evaluation index selection judgment process.
..

(Effect of evaluation index selection judgment process)
Even if multiple evaluation indexes appear, it happens in various places that you do not know which evaluation index to look at. For example, even with human dogs, various numbers come out, but it is important to be careful about these numbers, and the doctor tells you that, and then you should be careful about your diet. I will put it on and pay attention to various things.

In the first embodiment, the importance is transmitted by referring to the table on a text basis, but this is sufficient if the pattern is limited. However, as the number of various cases increases, it is required to be able to deal with various patterns. After going through this process, there is a merit that which of the many evaluation indexes calculated by the information processing system is important can be digitized and centrally managed.

In particular, if you manage with a number of evaluation indexes and a set of dates, it will be more convenient. For example, if you manage with a table that the evaluation indexes up to importance 5 are 5 for each date and investor, It is stored in the storage unit 33. It will be immediately available for KPI measurement of Mr. Z, who has made similar purchases and sales by matching multiple evaluation index sets of similar levels in the past.

By recording such data as learned data, it can be expected that the more data there is, the more the accuracy of KPI will improve. These will change over time, and Mr. A's KPI will also change. Due to the accumulation of past data, how the KPI six months ago and the current KPI have changed, and Mr. A's KPI itself has enough to change the first level KPI from the trading profit / loss ratio to the unrealized profit ratio. It is to obtain, and a special effect that makes it easy to catch the change can be expected. Of course, if the information processing system determines that it is important for those investors A, they are always charted on the dashboard and the transition is displayed so that the change in investment results can be felt. It may be, and it is very effective.

(Specific example of evaluation index selection judgment process)
(Specific example 1)
This is a specific example of trading data subject to aggregation by investor. For example, Mr. A's change in KPI between 2020 and 2019 is a concrete example.

(Specific example 2)
This is a specific example of trading data to be aggregated by investment target. For example, what is an important technical index related to the technical index of issue A that has a strong relationship with profit and loss?

(Specific example 3)
This is a specific example of trading data subject to aggregation by period. For example, what are the changes in KPIs in the first half and the second half of 2020?

(Specific example 4)
It can also be used as article data as to how the profitable standards have changed between the first half and the second half of 2020.

(Specific example 5)
In addition to the example of the upward revision mentioned above, there are also stocks and investors whose technical indicator values are KPI. For example, it is sufficient to be able to obtain data such as stock A is compatible with the stochastic oscillator of the technical index value, and the purchase data purchased when the stochastic oscillator is upward and exceeds 20% has a very high probability of winning. You can expect it.

(Explanation of FIGS. 80 and 81)
In FIGS. 80 and 81, V0 is a table that stores the conditions under which the trading data table has been created in the trading data condition table.

V1 is an evaluation index calculation table, which is a table displaying a list of evaluation indexes derived from trading data and target profit / loss created under the conditions determined by V0. The evaluation index calculated by the information processing system is ●, and the evaluation index not calculated by the information processing system is ×.

V2 is the weighting of the profit and loss level. As has been reported many times in the first embodiment, the total profit / loss level is a comprehensive index (trading profit / loss + unrealized profit / loss), so its importance is high (177, 178, 191, 215). As the level goes down, the level of detail increases, but the degree of influence on the whole decreases. If this is quantified concretely, it will be as shown in this table. It is self-evident, but it becomes clear when it is quantified.

In V3, the evaluation index that was ● in the evaluation index calculation table (that is, the evaluation index calculated by the information processing system in the process) is compared with Mr. A and the investor average, and Mr. A is excellent. For example, if it is positive or inferior, the negative divergence rate will increase. However, there is an inverse correlation index, and there is also an evaluation index that is negative if it is excellent and positive if it is inferior. For example, the higher the loss loss rate, the more negatively the profit and loss is, and it is necessary to weight this as an inverse correlation.

In V4, the highest evaluation index of the important index is set as the most important evaluation index (KPI highest importance rank 1) according to the important index, and the lower the importance thereafter, the lower the important index. Even in the first embodiment, the evaluation index has importance from time to time, and in particular, the importance changes depending on the person and time. By storing these tables in the storage unit 33. The changes in Mr. A's KPI and the numbers of other evaluation indicators are also saved, and it is possible to immediately output whether or not improvements have been made from the KPI one year ago.

(Specific example 1 of the evaluation index selection judgment process)
There are various methods other than the above scoring method. For example, if a profit / loss and related evaluation index importance score table is created, the important evaluation index will be determined immediately after the target profit / loss is determined. The accuracy will be improved by updating the importance score table from time to time (see Fig. 83).

The display method is the same as the display step of each step (for comparison on average, refer to each display step such as a radar chart).

(Definition of display method of evaluation index)
Examples of the evaluation index display method include figures, tables, numerical data, graphs, charts, and texts. Display such as comparison and ranking is also included in these display methods. In addition, the generated data is devised so that it can also be used as article data.

(Issues on how to display evaluation indicators)
It is difficult to understand what it means if it is just a display of numerical data of evaluation indicators. Reading the data takes some getting used to and may not make sense. Especially in the case of article data.

(Action of evaluation index display method)
The information generation unit 3021 calculates various evaluation indexes, but processing is required to display them in an easy-to-understand manner. For example, to give an example of creating a graph, if it is an evaluation index derived from component trading data, the graph created with the component on the horizontal axis and the evaluation index calculated on the vertical axis is easy to understand at a glance. You will also be able to visually understand comparisons and rankings.

(Effect of evaluation index display method)
The display method changes greatly depending on the combination of evaluation indicators, aggregation targets, goals, etc., which has the effect of promoting understanding at a glance for users.

(Specific example of display method of evaluation index)
For example, in the case of an evaluation index calculated by the information generation unit 3021 from the component trading data for each year based on the trading data to be aggregated by Mr. A, the trading profit / loss in 2016, the trading profit / loss in 2017, and the trading profit in 2018. The trading profit and loss is displayed in a graph. The transition is also easy to understand, which has the effect of promoting understanding at a glance. The information generation unit 3021 displays, for example, the trading profit / loss of stocks in 2020, the trading profit / loss of FX, and the trading profit / loss of virtual currency by calculating the evaluation index for each investment target of the trading data subject to aggregation by period of 2020. By setting the horizontal axis as the investment target and the vertical axis as the trading profit / loss amount, it is possible to see at a glance which investment target has increased profits in 2020. You can achieve effects that cannot be obtained simply by enumerating numbers. For example, in the case of an evaluation index calculated from component trading data for each investor based on the aggregated trading data of issue A. The buying price and selling price of Mr. A, the buying and selling price, the buying and selling price of Mr. B, the buying and selling price, the buying and selling price of Mr. C, and the trading profit and loss are displayed on the chart. The transition is also easy to understand, which has the effect of promoting understanding at a glance. For example, in the case of an evaluation index calculated from the unrealized gain / loss of the aggregated trading data of the A issue, the bid price and the unrealized gain / loss of Mr. A of the A issue are displayed on the chart. The current situation is also easier to understand, which has the effect of promoting understanding at a glance. Of course, if it is the above-mentioned evaluation index of all investors, it can be distributed as a news article and it will be easy to understand.

For example, in the case of the component trading data for each investment type of the trading data to be aggregated in 2020, the case where the winning profit, which is a component of the trading profit / loss, is evaluated. If you make a bar graph and the horizontal axis is the investor and the vertical axis is the winning profit, the winning profit in 2020 will vary considerably depending on the investor, and even if you buy the same brand, you will not earn with the people who make money. It has the effect of showing that there are people at a glance. Such articles are useful as news articles as well as article data such as which brand won in 2020.

(Specific example 2 of the display method of the evaluation index)
FIG. 79 shows the process of displaying the importance of the evaluation index. This step is a step of determining how to display the highly important evaluation index determined in the previous importance determination step in D101. D102 is a question of how to use the evaluation index with high importance, and it is displayed by comparison, ranking, and evaluation, and D103 is a comparison step, and the deviation rate is compared with the usage and the average. High evaluation indicators are likely to be buying and selling with different characteristics from other people, so make them stand out. D104 is a ranking step, and by further clarifying the difference from other people and ranking the bad points and the good points, it is possible to concretely grasp how bad and how good it is. Furthermore, by mainly using key performance indicators in the evaluation step, diagnosis step, and advice step, it is possible to highlight the differences and characteristics from others, which will contribute to the improvement of future investment results. be able to.

(Significance of the calculation and display step of the evaluation index)
For example, in response to the question of what is the calculation of the evaluation index that affected Mr. A's trading profit and loss, Mr. A's trading level trading data is extracted and aggregated, and the winning rate, winning profit rate, and losing loss rate are collected along with the trading profit and loss. , Etc. can be calculated. At this time, the winning rate can be automatically calculated from the trading level trading data, but the winning profit rate can be easily obtained by creating the winning level trading data. In that way, the necessary evaluation indexes are calculated, but there is a problem of the display method of how to convey these evaluation indexes of Mr. A. Among investors, there are various knowledge, experience, and know-how, and various display terminals. No matter how good the numbers, the good results, and the content to be improved, if it is difficult to understand or understand, it will be ruined. Display steps are set up to solve such problems.

(Problems of calculation display step of evaluation index)
Which valuation index affects the target profit and loss depends greatly on the way of buying and selling. The relationship between profit and loss and valuation indicators is complicated and may be interrelated. If the winning rate goes up, the winning profit margin goes down, the unrealized loss rate goes up, and there are various correlations. However, all the evaluation indicators are factors that have a great influence on the total profit and loss of the target.

Once the target profit and loss and the target to be improved are decided, the necessary evaluation index will be decided. This step is to calculate this necessary evaluation index from the trading data and profit / loss obtained in the previous steps, and how to display the calculated evaluation index to the user.

(Action of calculation display step of evaluation index)
Even if the same evaluation index is calculated, it is easy to understand if the display is suitable for the evaluation index and the problem, and the current state can be grasped, but if the display method is difficult to understand, the user cannot be informed. In order to display in an easy-to-understand manner, it is necessary to display the meaning of the evaluation index provided according to the task according to the task and the evaluation index.

(Effect of calculation display step of evaluation index)
A simple list of evaluation indicators is difficult for users to understand, and it is difficult to judge how to change them. For example, even if one win rate is expressed as 60%, nothing will sound, but the KPI (Key Performance Indicator) for current users is the win rate and the loss loss rate, and "Your current win rate". Is 60%, the winning profit rate is 7%, the losing loss rate is 8%, and the losing loss rate is higher than the winning profit rate, so the assets are not increasing easily. The winning rate is important, but the losing loss rate is 5%. If it is an expression such as "Why don't you try to hold it down? Your profit will increase by 500,000 yen a year." It becomes clear what to do. One expression method can make a big difference. In this step, it is not a list of data, but the most important evaluation index obtained in the selection step is used, and it is very effective for investors to output indispensable information suitable for each user. .. For investors, it has the effect of significantly changing investment behavior.

(Specific example of calculation display step of evaluation index)
(Specific example 1)
The chart display is excellent for displaying various evaluation indexes of the trading data to be aggregated by investment target. The chart display is very easy to understand for the technical index values of trading data to be aggregated by investor and the evaluation indexes of performance data.

(Specific example 2)
For example, the winning rate of trading by issue A in 2020 and the trading profit composition ratio of issue A are the trading data subject to aggregation by period in 2020, the trading data by component for each issue, and the trading profit / loss level trading data. It is an evaluation index that can be derived for the first time.

It is necessary to appropriately derive from the database the issue of what percentage of the winning rate of buying and selling by stock A of the day trading investment type group in 2020. Such data is highly newsworthy and can be said to be one of the data that can be distributed as an article.

As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated, and an evaluation index according to the purpose is calculated. Therefore, even in this step, various conditions and various forms of evaluation indexes can be easily displayed. Although this step is only one step in FIG. 102, since the evaluation index has been determined by a series of cooperation, it is possible to display many forms of the evaluation index mentioned in the present specification.

(Definition of evaluation index calculation chart display step)
Among the items listed in the calculation of the evaluation index, the chart display is particularly excellent for the evaluation index according to the purchase date, sale date, and holding period of the brand. As shown in FIGS. 103 to 106, it is possible to display the display in an easy-to-understand manner at a glance. It is significant that the chart you are used to seeing is displayed along with the situation in which you are placed, the difference from others, and the situation of other brands.

(Problems of conventional technology)
Chart display is a very familiar display method for those who are interested in investment products. However, in most cases, it is not personalized, and it is the mainstream that everyone displays the same chart for the same brand, and there are very few or no personalized chart displays for each individual. In particular, there is no chart that shows the material for judging whether the purchase decision was correct or the trend of other stocks during the holding period and the same period according to one's own buying and selling (Fig.) 103 to 106 are just examples.)
(Action of evaluation index calculation chart display step)
The information processing system can display a personalized chart for each individual, and the chart displays the purchase date and stock price of investor A, as well as various evaluation indexes (for example, purchase). Investors by displaying at least one evaluation index, such as changes in technical index values after purchase, changes in corporate performance after purchase, behavior of other investors after purchase, and trends of other stocks after purchase). The purpose is to contribute to various judgments by displaying on the chart the evaluation indicators that have an impact on the investment profit and loss of.

(Effect of evaluation index calculation chart display step)
For investor A, the chart display according to the situation of each individual and the situation of the brand will be the chart display according to his own situation, and the technical indicators and investment products that he cannot manage by himself will be displayed. You can centrally manage the financial status and rights status, and as one of the judgment materials, you can see the judgment contents of the information processing system, and also see the trends of other investors that contribute to investment decisions. You can expect a special effect that you can do it.

(Specific example of calculation chart display step of evaluation index)
FIGS. 103 to 106 are examples, and various patterns can be considered, such as those that capture changes in corporate performance and changes in technical indicators. Here, for example, technical index values and corporate performance and charts are displayed together everywhere, but since they are linked to purchase data etc., they capture changes after purchase and are the same in the past. Give an example of trading with such technical index values, and provide information such as what kind of trade was done at that time, whether it was successful or unsuccessful, and what should be done to be more successful. By doing so, it is possible to display a personalized chart tailored to each individual. The definition of personalization is not only that different charts are displayed for each individual, but it is important that information is provided according to the buying and selling of each individual for the purpose of how to improve the investment profit and loss of each individual. .. The definition of the valuation index is limited to the valuation index that has an influence on the investment profit / loss. There is a major premise that it will be displayed on the chart.

(Definition of a personalized chart that evolves in stages)
A chart that is personalized for each investor is defined as a personalized chart. First, the main premise is a chart linked to trading data, and for example, a case where it is linked to unrealized profit / loss level trading data of the second profit / loss level trading data is assumed. In other words, it is defined as a chart that is linked to the stocks held and that displays an evaluation index that affects the investment profit / loss that is related to the purchase date, sale date, and holding period. This is because investment profit / loss does not start unless the purchase date and purchase price are determined, so it is assumed that the purchase date and purchase price are displayed and managed. It is different from the kind of comparison between the so-called total profit / loss level valuation transition and the investment trust valuation transition.

(Problems of conventional technology)
For example, if there is a conventional technology that compares the rate of increase in valuation with the rate of increase in investment trusts, the comparison with the Nikkei 225, and the selection of similar investment trusts, this is the total profit / loss level. In terms of profit and loss level, it is the first level. Even if you know the whole picture, you can't deny it individually, so you can't deny the rough feeling. In order to evaluate the investment of investors in more detail, it is almost invisible unless we take another step. In terms of profit / loss level, it is the second level or higher, and the chart used for trading profit / loss level trading data and unrealized profit / loss level trading data is the minimum necessary condition for personalized charts. In addition, there is a premise that the issue is linked to the purchase date (or purchase price) and that the evaluation index that affects the investment profit or loss is displayed. A chart of stocks held or stocks that have already been sold (or stocks that are about to be purchased) based on such assumptions is a personalized chart.

(The action of personalized charts that evolve in stages)
Personalized charts will gradually evolve. For example, in the case of a personalized chart of holdings, the first level is to calculate and display the evaluation index that affects the investment profit and loss of investors, and the second is to display or manage the purchase price and purchase time. Level, current price, current is displayed at the 3rd level, evaluation index based on transaction data such as current price increase / decrease rate and holding period is calculated and displayed at the 4th level, similar to own past trading The fifth level is to extract trading data and display it, the sixth level is to display the buying and selling behavior of other investors at the same time and at the same time, and the rate of increase / decrease after purchase of other investment targets at the same time. Is defined as the 7th level, and the 8th level is defined as providing information that contributes to investment profits and losses by capturing changes in business performance and changes in technical index values after purchase. The level of gradual evolution is displayed in stages, but this is just one example, and the upper stage is not necessarily a more evolved form. I have presented one step to make it easier to understand how personalized the chart is.

(Effects of personalized charts that evolve in stages)
Personalized charts produce a variety of effects. It is a chart that changes according to one's own situation, and this information is sequentially accumulated in the database. This means that after the stocks held are sold, the trading data remains as a history, and that data is inherited by the trading profit / loss level trading data. As the fifth level information above, it will now be possible to use it as part of the information on the stocks held. This effect also has a significant effect. This means that past failures and successful experiences can be referred to at any time according to the current situation, and will be utilized in the judgment of the stocks currently held. Therefore, a truly personalized chart refers to the fifth level and beyond. The level up from here is the true value.

(Specific examples of personalized charts that evolve in stages)
103 to 106 are specific examples.

(Action of evaluation index calculation step)
With 2020 as the extraction condition, create trading data to be aggregated by period of the 2020 day training type group, create trading profit / loss level trading data (you can have it in the previous process), and the issue is A issue. It is calculated by creating component trading data, deriving the number of trading and the number of wins from the trading data, and deriving the winning rate.

In the case of machine learning, the process of machine learning the trading data determined as issues, necessary evaluation indexes, and uses (ranking, comparison, diagnosis, evaluation, advice) Become. It can be with or without teacher data. By inputting cases like the above concrete example, you will be able to learn and answer various tasks.

(New method of calculation display step of AI machine learning evaluation index)
The AI machine learning evaluation index selection step is performed through the following process.

(Significance of the evaluation index automatic selection process)
The above-mentioned automatic creation step of aggregation target trading data is one step of the automatic trading data creation process, but the target trading data is determined through the creation of trading data for each component and the creation of profit / loss level trading data. The process of automating the identification of the evaluation index to be calculated by the information processing system is the process.

(Issues in the process of automatically selecting evaluation indicators)
For users and administrators, the challenges they need to change from time to time. It would be convenient if trading data and evaluation indicators could be created automatically according to the required issues. As described in the specific example of the automatic creation step of the trading data to be aggregated, once the issue is decided, the trading data to be aggregated is decided, the trading data for each component is decided, the profit / loss level trading data is decided, and it can be calculated by the information processing system. The evaluation index is also decided. By determining these, the task can be achieved by being able to determine the use of whether to evaluate, compare, rank, diagnose, or give advice according to the task.

It may be done by AI, it may be automated by a program, or it may be referred by a table.

(Action of evaluation index automatic selection process)
If there is a problem, the above-mentioned trading data to be aggregated is determined, and if it is necessary to classify and aggregate the trading data to be aggregated according to some criteria, trading data for each component is created. Profit / loss level Move on to the creation of trading data (the order may change).

Since the profit / loss level of which profit / loss (or average trading profit / loss ratio (ROI average)) is to be improved is also decided at the time of the issue, create trading data at the profit / loss level and create the profit / loss level. By calculating various evaluation indexes that affect the profit / loss level based on the trading data, the underlying trading data and evaluation indexes can be automatically created.

By machine learning using AI, machine learning of evaluation indexes that affect profit and loss, memorizing various patterns, and accumulating trained data, this set of evaluation indexes can be this number. For example, it will be possible to make the best judgment by improving this evaluation index in order to improve profit and loss. The more the database is enriched, the more opportunities to learn the relationship between the evaluation index set and profit and loss, and various effects can be expected from the learning effect. Unprecedented findings can also be obtained (see FIG. 82).

(Effect of automatic evaluation index selection process)
It is easy for anyone to present a visible task of what they want to know. Once this issue is determined, the required trading data and the required evaluation index are calculated by the information processing system, so that a special effect can be expected for both the user and the administrator. This evaluation index calculated by the information processing system may be used in the following steps (after the evaluation step).

(Specific example of evaluation index automatic selection process)
Except for those mentioned in the step of automatically creating trading data to be aggregated, there are the following specific examples.

(Specific example 1)
When trading using the four seasons report, if the issue has the highest average trading profit margin, create the trading data to be aggregated by reference medium, extract and specify the four seasons report with the reference medium, and specify. It is achieved by creating trading data for each issue of the trading data and calculating a ranking table based on the trading profit ratio with the trading profit / loss level trading data by the information processing system. Such a process may be machine-learned and achieved by AI, or it can be realized by creating a reference table for a combination of a task and the process and automating the process. What do you want to know about the reference medium = quarterly report, target profit / loss = trading profit, when you submit an issue in a form or questionnaire? = It is possible to automate or create a manual by using a question format such as a brand or a method of selecting from a pull-down menu. Of course, such data is one of the information that not only the individual but also the medium side wants.

(Specific example 2)
What is the average rate of return on the stocks purchased when the 25-day moving average deviation rate of the technical index exceeds -20%? For this issue, create trading data for aggregation by technical index, set technical index = 25-day moving average deviation rate, and buy and sell the extracted 25-day moving average deviation rate minus 20% or less. It is achieved by further extracting from the data, creating trading profit level trading data of the trading data, and calculating the average value of the evaluation index = trading profit ratio by the information processing system.

(Significance of display of evaluation index of trading data subject to aggregation by investment target)
For example, the display of the total profit / loss from the trading of S1 company stock, the average trading profit / loss ratio, the average number of days held, the winning rate, the unrealized profit ratio, etc. corresponds to the display of the evaluation index of the trading data to be aggregated by investment target.

(Technical issues)
These numbers are numbers that have never appeared in the world. This is because all the investment behavior of the investment target was wrapped in a veil.

(Action of display of evaluation index of trading data subject to aggregation by investment target)
The information processing system creates aggregated trading data by investment target (extracted, classified, aggregated based on the investment target), creates profit / loss level trading data (in any order), and from the trading data set. Display the evaluation index derived by the information processing system. Extracting trading data based on the investment target in the information system, creating profit / loss level trading data that can calculate the target profit / loss in the information system, and related to the profit / loss from the trading data set. For the first time, the numerical value of the target evaluation index can be calculated and displayed by linking the flow of using the related elements as the evaluation index and displaying the evaluation index calculated from the information system. It will be possible.

(Effect of displaying evaluation index of trading data subject to aggregation by investment target)
For example, it will be possible to grasp that the total number of lost stations in September due to the buying and selling of S1 company stock will drop in October, and (in this case, the concept for each period is necessary) skillfully manage S1 company stock. It will be possible to verify how people who buy and sell are doing, what is wrong with their own way, etc., and it is expected that the actual situation that was a black box will be clarified.

(Specific example of display of evaluation index of trading data subject to aggregation by investment target)
How many days are the average holding days of S1 company stock, how many people are buying and selling, how often are the holding people buying at what stock price, and the current unrealized gain is You will be able to see how many there are.

(Definition of display of evaluation index by trading data, which is a component of trading data to be aggregated by investment target)
The purchase date of the S1 company stock is one component. If the investment target trading data of S1 company stock is created by the information information system (extraction condition: investment target = S1 company stock) and the trading data is further extracted on 9/10 of the purchase date, Softbank will be on 9/10. A trading data set for purchasing stocks is created, and profit / loss level trading data is created depending on which profit / loss of the trading data set is targeted (the previous process is also possible), and the evaluation index that affects the profit / loss with the trading data. Is calculated by the information processing system, and displaying the evaluation index is called display of the evaluation index based on the component trading data of the trading data to be aggregated by investment target.

(Conventional issue)
For example, in the case of S1 company stock, many people purchased it on 9/10, and the total figures are usually announced in the market as trading volume and trading value. If the daily trading value is 10 billion yen, 10 billion yen is bought and sold. However, I don't know any more. It is information that does not appear in the world at all, such as who was selling and renting, how they were buying and selling, and how many people bought and sold today. However, for investors, once they understand the details, they can see how to improve and why they are losing money. In particular, if the actual situation of buying and selling becomes clear due to the existence of stocks, you will not be fooled and you will be able to take correct investment actions. The purpose of the information processing system is exactly there, and it is an invention that helps to remove the barriers and obstacles between savings and investment by clarifying the actual situation so as not to repeat erroneous investment behavior. ..

(Components of trading data to be aggregated by investment target Display of evaluation index by trading data)
I mentioned how to create it in the definition, but the most important thing is to display the evaluation index, but it can be displayed only after a series of flows. It is the display of this metric that can be achieved in collaboration with coherent computers and software, rather than disjointed.

(Effect of displaying evaluation index by trading data, which is a component of trading data to be aggregated by investment target)
For example, in the data related to buying and selling of S1 company in the previous example, if it is hypothesized that the trading value of 10 billion yen covers all buying and selling in the information processing system, it is the total of the purchase price and the sale price. Should be equal to the forehead. Originally, in addition to that, for example, the total trading profit and loss, the total unrealized profit and loss that increased today, the total loss amount in the case of winning rate and losing trade, the loss rate, the total profit amount in the case of winning trade, etc. Evaluation indicators should be able to be calculated and displayed. The social impact and the effect on investors by displaying these are immeasurable. It is not difficult to imagine that it will be a material for articles and news from various perspectives.

(Specific example of display of evaluation index by trading data, which is a component of trading data to be aggregated by investment target)
As described in many cases in this specification, to mention one, by extracting only 9/10 purchasers of S1 company stock and creating trading profit / loss level trading data, S1 company stock will be traded on 9/10. After that, the investor who bought the stock will be able to grasp the actual situation such as how much it sold, how long it kept holding, and how much the average profit amount of the sellers was.

(Definition of display of evaluation index by investor-specific trading data of aggregated trading data by investment target)
The display of the evaluation index based on the investor-specific trading data of the investment target aggregation target trading data is, for example, the investment target aggregation target trading data of S1 company stock (not necessarily S1 company stock or A brand). Extract, classify, aggregate, and create trading data based on investors, create profit / loss level trading data at the target profit / loss level, and influence the target profit / loss based on the relevant trading data set. It means to calculate a certain evaluation index by the information processing system and display the calculated evaluation index.

(Problems of conventional technology)
In the previous example, I told you that the trading value of S1 company stock is 10 billion yen and I do not know anything beyond that, but one of them is this process that can be understood from the perspective of investors. .. For example, Investor A bought for 3900 yen and sold for 4500 yen, Investor B bought for 4600 yen and sold for 4500 yen, and so on. , The process of grasping the actual situation.

(Specific example of display of evaluation index by investor-specific trading data of aggregated trading data by investment target)
Investment target aggregation Target trading data is extracted, classified, and aggregated based on investors, and the created trading data is used to create profit / loss level trading data at the target profit / loss level, and based on the trading data set. Therefore, the evaluation index that affects the target profit and loss is calculated by the information processing system, and the calculated evaluation index is displayed. If it is classified by investor, the investor is the S1 company stock. A is like this, investor B is like this, extraction by investor means extracting only investor A, and if investor is classified and aggregated, investor A aggregates a large number of trading data. .. However, although the numbers will be easier to see if they are aggregated, you must be careful that some evaluation indicators will not appear.

(Specific example of display of evaluation index by investor-specific trading data of aggregated trading data by investment target)
It is possible to create original data for articles such as who is the top investor in the average trading profit / loss ratio of S1 company stock, what is the secret of the investor with the highest winning rate in S1 company stock, and the average of S1 company stock. It is also possible to compare how to buy and sell in a standard manner and how to buy and sell at the top level of results.

(Definition of display of evaluation index by trading data by investment target (investment target))
For the sake of clarity, if the case of S1 company is explained here as well, the starting point of this step is that the component of the stock, which is a higher concept than the S1 company stock, is the S1 company stock. When you want to know the position of S1 company stocks among stocks, it is useful to display the evaluation index based on the trading data by component (investment target) of the trading data to be aggregated by investment target.

(Problems of conventional technology)
Assuming that S1 company stocks have a trading value of 10 billion yen a day, the higher-level concept of stocks is that funds of 2 trillion yen or several trillion yen a day are moving every day. This situation is also veiled, and although the trading trends by investor are reported by the Tokyo Stock Exchange, etc., the actual situation is hard to come out. In addition to S1 company stocks, various stocks are bought and sold every day, and even one day is enormous. However, when the actual situation of one of the S1 company stocks becomes clear, the whole picture will become clear. Indeed, it is the display of the evaluation index based on the trading data by component (investment target) of the trading data to be aggregated by investment target for that purpose.

(Components of trading data to be aggregated by investment target (investment target) Effect of display of evaluation index by trading data by investment target)
It is an important point to make stocks, which is a higher-level concept, into trading data to be aggregated by investment target. The profit / loss level is determined, the profit / loss level trading data is created by the information system, the evaluation index that affects the target profit / loss is calculated from the non-equal trading data by the information system, and the calculated evaluation index is the relevant. Displaying on the information system is this process. Among the stocks, S1 company stock has a trading profit weight of 7%, occupies the second weight after T stock, unrealized profit weight is 3%, turnover rate is slightly higher than average, and average holding. It will be possible to calculate and display evaluation indexes by the information processing system, such as the number of days being shorter than the average.

(Factors of display of evaluation index by trading data by investment target (investment target))
The position of S1 company stocks becomes clear in the whole of stocks, and broadly speaking, what kind of attractiveness does S1 company stocks have compared to other investment trusts, ETFs, virtual currencies, FX, etc. as investment targets? It also has the special effect of being able to display the datasets needed to create articles such as. In each case, data existed in the world, but it was not utilized, data will be utilized, and a way to solve social issues such as investment and savings problems and 20 million yen problems will be created. Is also a possible invention.

(Specific example of display of evaluation index by trading data by investment target (investment target) component of trading data to be aggregated by investment target)
Compared to 2019, which results were improved in 2020 compared to the characteristics of buying and selling S1 company stocks among stocks and investment targets such as stocks, investment trusts, ETFs, and virtual currencies. The actual situation will be clarified, such as how it was, which investment products are likely to succeed in buying and selling, and what kind of failures people who have failed have made.

(Definition of trading data below the trading profit / loss level)
The trading data below the trading profit / loss level indicates the trading data of each of the following levels required for the evaluation of trading.
(1) 2nd level trading profit / loss level trading data (2) 3rd level winning profit (or losing loss) level trading data (3) 4th level winning (or losing) pattern level trading data Improvement of trading profit / loss For such purposes, various things can be done by creating trading data below the trading profit / loss level and following the evaluation process, diagnostic process, advice process, comparison process, ranking process, and so on.

(Definition of trading data below unrealized profit / loss level)
The trading data below the unrealized profit / loss level shows the trading data at each of the following levels necessary for evaluating the holding status of the investment target.
(1) Second level unrealized gain / loss level trading data (2) Third level unrealized gain (or unrealized loss) level trading data (3) Fourth level unrealized gain (or unrealized loss) pattern level trading data For the purpose of improving unrealized gain / loss, etc. In this case, various things can be done by creating trading data below the unrealized profit / loss level and following the evaluation process, diagnostic process, advice process, comparison process, ranking process, and so on.

The terminal 2 presents the information generated by the information generation unit 3021 to the user. Each time data is exchanged, the data is exchanged with the storage unit 33, and various data are accumulated.

In addition, the information generation unit 3021 calculates an evaluation index with reference to trading data, compares and ranks investors with reference to the calculated evaluation index, and evaluates information indicating the comparison result and ranking of the investor. It may be generated as an index. The comparison here refers to comparing the evaluation index of the investor with the evaluation index of another investor, the average value of the evaluation index, and the like.

(Outline of processing of information presentation system 10)
FIG. 3 can be referred to as a diagram showing a processing outline of the information presentation system 10 according to the present embodiment. The processing outline of the information presentation system 10 will be described with reference to FIG.

(Step S301)
In the terminal 2 (either a user terminal or an administrator terminal is possible), the control unit 22 acquires investment product trading data from the operation reception unit 24 and the like, and the communication unit 21 transfers the trading data to the server 3. Send. As shown in FIG. 2, the generated data is also stored in the storage unit 33. Details of the trading data will be described separately.

(Step S302)
In the server 3, the control unit 32 receives the trading data from the terminal 2 by the communication unit 31. The information generation unit 3021 calculates an evaluation index from trading data. The control unit 32 transmits the calculated evaluation index by the communication unit 31 to the terminal 2 (whether it is a user terminal or an administrator terminal) as an evaluation result. As shown in FIG. 2, the generated data is also stored in the storage unit 33. Details of the evaluation index will be described separately.

(Step S303)
In the terminal 2, the control unit 22 receives the evaluation result from the server 3 by the communication unit 21, and causes the display unit 23 to display the evaluation result. As shown in FIG. 2, the generated data is also stored in the storage unit 33.

(Step S304)
In the server 3, the information generation unit 3021 diagnoses the user's buying and selling tendency from the evaluation index calculated in step S302. The control unit 32 transmits the diagnosed trading tendency as a diagnosis result to the terminal 2 by the communication unit 31. As shown in FIG. 2, the generated data is also stored in the storage unit 33.

(Step S305)
In the terminal 2, the control unit 22 receives the diagnosis result from the server 3 by the communication unit 21, and displays the diagnosis result on the display unit 23 (whether it is a user or an administrator). As shown in FIG. 2, the generated data is also stored in the storage unit 33.

(Step S306)
In the server 3, the information generation unit 3021 performs investor comparison and ranking from the evaluation index calculated in step S302. The control unit 32 transmits the comparison data and ranking data of the investor to the terminal 2 (whether it is a user terminal or an administrator terminal) by the communication unit 31. As shown in FIG. 2, the generated data is also stored in the storage unit 33.

(Step S307)
In the terminal 2, the control unit 22 receives the investor comparison data and the ranking data from the server 3 by the communication unit 21, and causes the display unit 23 to display the investor comparison and ranking. As shown in FIG. 2, the generated data is also stored in the storage unit 33.

(Step S308)
In the server 3, the information generation unit 3021 generates advice on the buying and selling of the investment product by referring to the trading data of the investment product, the evaluation index, the tendency of the user to buy and sell, the comparison data of the investors, the ranking data and the like. The control unit 32 transmits the generated advice to the terminal 2 by the communication unit 31. As shown in FIG. 2, the generated data is also stored in the storage unit 33.

(Step S309)
In the terminal 2, the control unit 22 receives advice regarding the buying and selling of investment products from the server 3 by the communication unit 21, and displays the advice on the display unit 23. As shown in FIG. 2, the generated data is also stored in the storage unit 33.

It should be noted that, in the server 3, various conditions are determined, the target profit / loss, the evaluation index is calculated, the evaluation index is selected, the score, etc. are stored in the DB, and the ranking data is performed by referring to the trading data to be evaluated. , Creation of diagnostic data and storage in the DB are executed by, for example, batch processing. The DB is set in the storage unit 33 of the server 3, for example.

It should be noted that a series of these data are accumulated in the DB for each user, and can be displayed at the request of the user, or the entire data can be extracted at the request of the administrator. These calculated generated data can be distributed as article distribution or can be sold.

(Definition of profit / loss level)
Regarding the profit / loss level, the total profit / loss level is defined as the first level, the unrealized profit / loss, and the trading profit / loss are defined as the second level, and the unrealized profit, the unrealized loss, the winning profit, and the losing loss are defined as the third level. The definition targets of the fourth level are unrealized profit above the benchmark, unrealized profit below the benchmark, unrealized loss above the benchmark, unrealized loss below the benchmark, winning patterns 1 to 3, and losing patterns 1 to 3. As mentioned above, there are four levels of profit and loss.

It should be noted that this leveling is only an example, and a part of it may be used or another index may be defined. The winning patterns 1 to 3 and the losing patterns 1 to 3 have already been described in the first embodiment and FIG.

(Definition of profit / loss level trading data)
With regard to profit / loss level trading data, the profit / loss divided into each level includes trading data that is the source of the profit / loss. For example, the second level trading profit / loss is based on the trading data in which the counter-trading is performed, and the unrealized profit / loss is based on the trading data in which the counter-trading is not performed. The winning profit of the third level is based on the trading data of the buying price <the selling price among the trading data of the counter-trading.

For example, in the case of profit / loss, the trading profit / loss of counter-trading is based on the traded trading data, and the unrealized gain / loss of non-counter-trading is based on the unrealized trading data. Trading profit / loss trading data is divided into trading profit data of winning (buying price <selling price) profit, losing (buying price> = selling price) loss trading data, and the like. In this way, dividing the trading data by profit and loss is an important process for calculating the evaluation index by the information processing system in the profit and loss level evaluation to be performed later.

(Definition of evaluation index by profit / loss level)
Divide the profit and loss level, divide the trading data accordingly, and define it as the profit and loss trading data by level. Then, the evaluation index calculated by the information processing system based on the profit / loss trading data for each level is defined as the profit / loss evaluation index for each level.

(Definition of profit / loss level evaluation index)
The profit / loss level evaluation index is an evaluation index calculated based on the profit / loss level trading data. For example, the evaluation index based on the trading data (trading profit / loss) in which the counter-trading was performed is the trading profit / loss ratio. The evaluation index based on the trading data of winning profit (winning profit) is the winning profit ratio.

(About collecting and processing)
Aggregation refers to aggregation, processing, or both. Among the evaluation indexes calculated by the information processing system from the trading data, some evaluation indexes will not be calculated if they are aggregated, and some evaluation indexes will appear only after processing the trading data set as it is. be. For example, the trading profit / loss ratio is the latter, the total purchase price is the former, and the necessary evaluation index is calculated by the information processing system according to the situation.

(Definition of components)
The component indicates an element included in the trading data to be aggregated. For example, when the trading data of Mr. A's investment product is aggregated, virtual currency, FX, stocks, etc. may be constituent elements, or specific stocks among stocks may be constituent elements. Investors, investment types, investment groups, etc. are also included in the components. When stocks are included in the total, investors, stocks, dates, etc. are also included in the components.

(Profit and loss level stage evaluation index)
The information generation unit 3021 looks at the trading data in terms of total profit / loss (first level), extracts the trading data depending on whether or not it is counter-trading (second level), and determines whether or not it is profitable. Is extracted (third level), and the trading data is further divided into patterns and extracted (fourth level). In this way, the information generation unit 3021 processes and recreates the trading data by a method of extracting the trading data step by step, and calculates each evaluation index. It should be noted that this is only an example, and it may be performed in two stages, three stages, a second level, or another division method.

(Definition of market price at time A)
In the case of each period, the time point that becomes the starting point is defined as the time point A (first time point), the market price at the time point A is defined as the market price at the time point A, and the valuation amount at the time point A is defined as the valuation amount at the time point A.

(Definition of market price at time B)
In the case of each period, the time point at which the end point is reached is defined as the time point B (second time point), the market price at time B is defined as the market price at time B, and the valuation amount at time B is defined as the valuation amount at time B.

(Definition of market price for benchmarks)
The market price corresponding to the benchmark is calculated by multiplying the rate of increase / decrease in the benchmark x (the bid price or the market price at time A). The benchmark rate of increase / decrease indicates the rate of increase / decrease based on the benchmark value at the time of purchase or A.

(Definition of aggregation target)
The criteria such as investment target, investor, period, profit and loss, etc. are aggregated. For example, if the target of aggregation is an investor, not only individual investor group, institutional investor group, individual investor A, institutional investor B, etc., but also investor type group centered on short-term trading, medium- to long-term holding investment Includes investor types such as investors in the house type group, and is subject to aggregation of trading data. If the target of aggregation is an investment target, each issue, each issue group, each product, and each product group will be aggregated. If the aggregation target is a period, the aggregation target is May 2018, every year, every week, and so on. If the target of aggregation is profit or loss, trading profit or loss, unrealized profit or loss, and total profit or loss are subject to aggregation. If the aggregation target is an investment target, the aggregation target is for each issue such as A issue, or for each product such as stocks and FX. Further, if the aggregation target is an advisor, each advisor such as the advisor A and the advisor company A can be aggregated. It is also possible to aggregate the securities companies that are being used, and aggregate by securities company A and securities company B. The medium can also be counted. It is also possible to aggregate the media referred to by media such as quarterly reports, personal blogs, and Twitter. In addition, it is also possible to put together the aggregation targets that are separated.

(Definition of trading data to be aggregated)
Trading data is divided by investment target, investor, period, profit / loss, investment type, adviser, securities company, medium, etc., and the divided trading data is defined as aggregated trading data. It is also possible to collect and reclassify the disparate aggregated trading data.

(Definition of component trading data)
The above-mentioned aggregated trading data or profit / loss level trading data is divided into components such as investment target, investor, period, profit / loss, investment type, adviser, securities company, medium, and technical index value. Trading data is defined as component trading data. The component includes the input items added in the first step and the second step, which indicate the items that can be managed in the database, and refers to the table items (including the related items) of the trading data.

(About investment target)
Includes stocks such as company S stocks, investment trusts, stocks such as ETF bull funds, stocks such as FX yen dollars, and virtual currency stocks. In addition, the stocks may be grouped and the aggregation target may be divided into a trader stock group, an excellent stock group, a high dividend stock group, etc., or an index investment trust group, a robot fund group, etc. may be aggregated. Furthermore, products, product groups, etc. are also included in the total. The information generation unit 3021 divides, for example, trading data for each aggregation target such as virtual currency, FX, and stocks, aggregates each of them, and calculates various evaluation indexes.

(About investors)
For example, if the target of aggregation is an investor, the individual investor group, the institutional investor group, the individual investor A, the institutional investor B, the investor type group centered on short-term trading, and the medium- to long-term holding investor type group. The target of aggregation is trading data by investor type such as investors.

(About the period)
For example, if it is a period, it is divided into annual trading data if it is one year, monthly data if it is one month, weekly trading data if it is one week, daily trading data if it is one day, 2019 trading data, etc. ..

(Profit and loss)
For example, in the case of profit / loss, the trading profit / loss of the counter-trading is the traded trading data, the unrealized gain / loss of the non-counter-trading is the unrealized trading data, and the trading profit data of the winning (buying price <selling price) profit among the trading profit / loss trading data. Losing (buying price> = selling price) Loss It is divided into trading data and so on. Dividing the trading data by this profit / loss is an important process for calculating the evaluation index by the information processing system in the profit / loss level evaluation described later.

(What kind of generated data can be produced)
There are various types of generated data generated by an information generation system (information generation device). I give a number of concrete examples, but one of them is article data. The data generated by the advice generation unit 321 includes various evaluation indexes generated from trading data, and comparison data, ranking data, diagnostic data, evaluation data, and advice data using these are also useful as news articles. It contains a lot of data. The generated system is the same, and the generated data includes, in addition to article distribution data, problem solving data, ranking data, comparison data, evaluation data, advice data, etc., and is not limited to this.

There are many and a wide range of investment issues. As we have seen, various investment issues will be solved by linking with trading data. This information generation system can generate advice for investment, and if turned inside out, it can generate data that can solve investment problems. The advice to raise the winning percentage for Mr. A and raise the winning profit margin is to reverse the same process that Mr. A's investment task is to raise the winning profit margin, and in order to raise it, let's do this. I'm just following. Therefore, the advice generation system can be used as it is for a system that solves investment problems.

The steps from the sixth step to the eleventh step are defined as operation steps. Up to the fifth step, the following has been decided. Up to the fourth step, the determination of the target trading data, the target profit and loss, the evaluation index calculated by the information processing system, and its selection. What to do using the evaluation index calculated by the information processing system in order to improve the target profit and loss is the operation step after this sixth step. Whether to evaluate using the evaluation index (this step), whether to compare the evaluation index with the comparison target, whether to rank based on the evaluation index, whether to make a diagnosis using the evaluation index, or whether to give advice using the evaluation index. It is a step of what to do, such as whether to display using an index, and what to do for the target profit and loss is the step after this sixth step.

First, the sixth step evaluation process (H-100 in FIG. 77) is divided into an evaluation step (H-101) and a display step (H-103). The issue is how to evaluate and how to display it using the evaluation index calculated by the information processing system in order to improve the target profit and loss.

For example, in order to improve the trading profit and loss, what kind of trading has been carried out is evaluated by the numerical values of the evaluation indexes such as the winning rate, the winning profit rate, and the losing loss rate. If the evaluation index improves, the trading profit and loss will also improve.

(Definition of evaluation method)
FIG. 32 is a diagram showing a procedure of the evaluation method according to the present embodiment. As shown in FIG. 32, there are the following five evaluation methods for evaluating the aggregation target using the calculated profit / loss level evaluation index.
(1) Trading status evaluation (2) Trading status and holding status evaluation (3) Holding status evaluation (4) Linked holding status evaluation (5) Linked trading status and holding status evaluation These evaluation methods are subject to aggregation by period. It can also be applied to evaluations based on trading data and evaluations based on trading data aggregated by investment target.

The evaluation process is performed through the following process.

The first step is the acquisition step of trading data. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component. The fourth step is the step of creating profit / loss level trading data. The fifth step is the calculation and selection step of the evaluation index. The sixth step (this step) is an evaluation process (divided into an evaluation step and a display step).

Based on the evaluation index calculated by the information processing system, the trading status, holding status, etc. of the target are evaluated by any of the following evaluation methods (1) to (5). Further, displaying these evaluations by an appropriate display method may be performed in the relevant step or may be performed in the eleventh step. Examples include tables, pie charts, components, bar charts, radar charts, etc.

(Old method of evaluation process) To summarize the terms, as shown in FIG. 77, the evaluation process for performing evaluation is divided into an evaluation step and a display step. Hereinafter, the evaluation process will be described (H-100 in FIG. 77).

(Old method of evaluation process)
FIG. 21 is a diagram showing a comparison of evaluation process methods according to the present embodiment. In the old method of the evaluation process, the advice generation unit 321 evaluates the buying and selling of investment products by acquiring basic data from the trading data and calculating an evaluation index from the basic data. For example, the advice generation unit 321 acquires the total profit / loss from the trading data and calculates the evaluation index with reference to the total profit / loss. In addition, the advice generation unit 321 calculates an evaluation index according to the level stage of profit and loss. In the old method, the evaluation index is calculated and the decomposition formula of each profit and loss is presented.

(Issues in the evaluation process)
In the new method of the evaluation process according to the present embodiment, a process is presented in which the trading data is extracted (or classified, aggregated, processed) in several stages, and then the trading and holding of the aggregated object are evaluated. ..

The old method and the new method will be explained in comparison. First, the former acquires the trading data of investment products and acquires the basic data from the acquired trading data, while the latter process of creating the aggregated trading data is to evaluate the aggregated object (evaluation index). It is to extract (or classify, aggregate, process) trading data with the purpose of creating it. Further, the latter process of creating profit / loss level trading data is a process of extracting and processing aggregated trading data according to the profit / loss level, and creating a plurality of various trading data. Then, since it is based on various trading data extracted (or classified, aggregated, and processed), trading data by period, trading data by investment target, and the like are created. Through the process of the second step and the third step (or the second step) of the creation of the trading data to be aggregated and the creation of the component trading data, the trading data to be worked and the target profit and loss are determined. In the fifth step, it is decided which evaluation index is calculated and selected by the information processing system. It is possible to evaluate the trading data to be evaluated by using the trading data of the fixed work target, the target profit / loss, and the evaluation index calculated and selected by the information processing system. By displaying the evaluations made by an appropriate display method, the evaluations can be understood at a glance. One of the operation steps is an evaluation step, which may include displaying the numbers so that they are displayed in a suitable display method (may be summarized in the eleventh step) instead of simply enumerating the numbers.

By linking with the database, the usage is expanded, the evaluation index is expanded, and it is possible to perform deep evaluation.

(Action of evaluation process)
In the aggregation target trading data creation process, the information generation unit 3021 creates aggregation target trading data by period, aggregation target trading data by investor, and the like. The information generation unit 3021 further processes and extracts each aggregation target trading data. In the process of creating profit / loss level trading data (1st to 4th levels), profit / loss level trading data is created based on each aggregated trading data. The trading data to be evaluated in the sixth step is determined by the trading data to be aggregated in the second step, the component trading data in the third step, and the profit / loss level trading data in the fourth step (see FIG. 77). However, in this process, the profit / loss level trading data may be created only at the first level or only at the second level. If it is only the second level, it is the creation of trading profit / loss level trading data of the trading data (or component trading data) to be aggregated. In the evaluation index calculation process, the information generation unit 3021 calculates an evaluation index for evaluating the calculated profit / loss from the profit / loss level trading data. Again, as described in the previous process, it is calculated by the information processing system of the evaluation index such as the total profit / loss, the total profit / loss ratio, and the current valuation amount calculated by the information processing system from the trading data of the first level total profit / loss level. Or, it refers to an evaluation index such as the total trading profit / loss value calculated by the information processing system from the second level trading profit / loss level trading data or the average trading profit / loss ratio. Depending on these levels, the evaluation index calculated by the information processing system changes, and the amount also changes. Further, in the holding and trading evaluation process of the aggregation target, the information generation unit 3021 evaluates the holding and buying and selling using the calculated evaluation index. For example, it refers to evaluating the holding status and trading status using figures such as the total profit and loss, which is the first-level evaluation index of Mr. A, and the principal and current valuation amount. The same applies to the evaluation of the trading status from the evaluation index of the total trading profit / loss amount of the second level calculated by the information processing system from the trading data of the A issue (trading data to be aggregated).

Of the trading data, what kind of trading data is targeted is the process of the second step and the third step. The fourth step is the stage of valuing the trading data at what profit / loss level, which determines which trading data is evaluated in order to improve which profit / loss. Further, by calculating the evaluation index constituting the profit / loss by the information processing system, the evaluation index that influences the result of the profit / loss is calculated by the information processing system. With reference to the evaluation index calculated by this information processing system, the trading status and holding status of the evaluation target will be evaluated. These evaluations will be displayed in an appropriate display method. According to this series of flow, the target evaluation target, the target profit / loss, and the evaluation index related to the target profit / loss are determined, and the evaluation index of the target profit / loss of the evaluation target can be used to evaluate and display the system.

(Significance of evaluation process)
The valuation process includes a process of creating trading data to be aggregated, a process of creating profit / loss level trading data, and an evaluation process of trading and holding of the subject to be aggregated through a process of calculating an evaluation index using the trading data.

As mentioned above, there are 6 steps from the acquisition of trading data in the 1st step to the evaluation in the 6th step, but the order may be reversed or the steps may not be taken. If omitted, it is included in this process. The same applies when a problem solving step is inserted.

(Effect of evaluation process)
Compared to the old method, the new method of evaluation process has a much wider range (expanded to trading data by period, investment target trading data, etc.) and deeper (separation and interlocking of holding and trading evaluation). , Profit and loss level stage evaluation, etc.), the range of expression has expanded (display step and display step of the eleventh step), and once the evaluation target has been decided, the process of evaluation from various aspects has been clarified. For example, in order to evaluate the trading profit / loss of Mr. A in 2019, the trading data to be aggregated by Mr. A is created, and the component trading data for each year of Mr. A is created with the year as a component. As a result, Mr. A's trading data for FY2018, FY2019, and FY2020 is created (steps 2 to 3). In order to evaluate the trading profit / loss, trading data below the trading profit / loss level is created for each of Mr. A's FY2018, FY2019, and FY2020. Among them, by creating the trading profit / loss level trading data for 2020, the trading profit / loss amount (total value) of Mr. A in 2020 is determined. For example, if it is 1 million yen, this 1 million yen will be the amount of money earned in various transactions in 2020.

A goal has been set to increase Mr. A's trading profit of 1 million yen in 2020 in 2021 (steps 2 to 4). Trading data (for work) that produced a trading profit of 1 million yen in 2020. How do you evaluate the trading data (Fig. 76, Fig. 77)? Is the reason why he earned this 1 million yen at the next stage, and the factors that influence it, such as the principal (valuation amount at the beginning of 2020), the valuation amount at the end of 2020, the number of transactions, the winning rate, the winning profit and the losing loss, etc. Various evaluation indexes, which are decomposition elements, components, and related elements that are the reasons for generating profits, are calculated by the information processing system (fifth step). Using these evaluation indexes calculated by the information processing system, the trading situation of Mr. A in 2020 is evaluated (sixth step), and the trading profit of Mr. A in 2020 of 1 million yen is that of Mr. A in 2020. Since the constituent elements of the issue (evaluation index such as the trading profit of the A brand of 100,000 yen) can be calculated from the trading data of the trading profit by the information processing system, the A brand is 100,000 yen out of the trading profit of 1 million yen. Evaluation indexes such as, B brand is 200,000 yen, etc. can also be calculated by the information processing system. A pie chart is suitable for displaying the evaluation indexes calculated by the information processing system in an easy-to-understand manner. This process is the display process.

(Specific example of evaluation process)
For example, the trading data of Mr. A in 2019 is used as the trading data to be aggregated by period, four-stage profit / loss level-stage trading data is created, and various evaluation indexes are calculated by the information processing system. This makes it possible to evaluate Mr. A's buying and selling in 2019 and the resulting assets held at the end of 2019 from various aspects.

For example, if the trading data of S company stock in 2019 is used as the trading data to be aggregated by period, four stages of profit / loss level stage trading data are created, and various evaluation indexes are calculated by the information processing system, the S company stock 2019 It is possible to evaluate the total profit / loss of the year, the trading profit / loss, and the resulting unrealized profit / loss at the end of 2019 from various aspects.

For example, when evaluating the winning profit of Mr. A's investment product, it becomes clear that the stock is winning, but the profit is not fixed in the virtual currency and investment trust. By evaluating the unrealized loss of M company stock by investor, it becomes possible to evaluate the holding status of many investors. That is, there is a special effect that the prior art does not have.

As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated, and an evaluation index according to the purpose is calculated. Therefore, even in this step, various objects can be easily evaluated under various conditions and various forms of evaluation indexes. Although this step is only one step in FIG. 102, since the target and the evaluation index have been determined by a series of cooperation, it is possible to evaluate many forms of the target mentioned in the present specification.

For example, in order to evaluate the trading profit / loss of issue A in 2020, create the trading data to be aggregated for issue A (collect the trading data to be aggregated for Mr. A, Mr. B, Mr. C, etc.) and only the trading data of issue A. Is extracted), and the year component trading data of issue A is created with the year as a component. As a result, trading data for the A issue in FY2018, FY2019, and FY2020 is created (steps 2 to 3). In order to evaluate trading profit / loss, trading data below the trading profit / loss level is created for each of the A issue in FY2018, FY2019, and FY2020. Among them, by creating trading profit / loss level trading data for FY2020, the trading profit / loss amount (total value) of issue A in FY2020 is determined. For example, if it is 50 million yen, this 50 million yen will be the amount of money earned from various trading of A brand in 2020.

The profit / loss of 50 million yen in trading profit of issue A in 2020 is decided (steps 1 to 3), and how to evaluate it is the next step, which is the reason why we earned this 50 million yen. , The information processing system calculates the decomposition elements, components, and related elements that are the reasons for the trading profits such as the number of transactions, the winning rate, the winning profit, and the losing loss, which are the components (4th step). ..

It is a process of evaluating the trading status of the A brand in 2020 with the evaluation index calculated by the information processing system. Further, for example, if an investor is used as a component based on the above-mentioned 2020 A issue trading data, the 2020 A issue is divided into A's trading data and B's trading data. By using profit and loss as trading profit and loss and using the number of trades as an evaluation index, it is effective to make it clear at a glance who earned the most and how.

A pie chart is suitable for clearly displaying who earned the trading profit of stock A in 2020, and the person who earned the most is each evaluation index (number of trading, number of days held, winning profit rate and losing loss rate). Etc.) is made into a hexagon, and the evaluation process is to select an appropriate expression method such as which number is better than the average.

The target trading data is determined by the combination of the trading data to be aggregated and the component trading data. The target profit and loss is decided in the third step. In the fourth step, the evaluation index that affects the profit and loss is calculated by the information processing system. Various evaluations are performed using the evaluation index calculated by the information processing system. The sixth step is how to express the evaluation.

(Definition of transaction data evaluation method)
There are several methods for evaluating transaction data (trading data in a narrow sense), but there are viewpoints of which profit and loss level to evaluate and which mathematical function is used for evaluation. For details on which profit / loss level to evaluate, refer to the section of profit / loss level evaluation index.

Here, we will explain which formula is used for evaluation. Transaction data (trading data in a narrow sense) can be evaluated by calculating the value represented by an expression such as a function based on the value associated with the variable.

Give a case of total profit / loss level, which formula is used to evaluate transaction data.

[Calculation method 1 (including the turnover rate of winning trades and losing trades)]
Total profit / loss = {(win rate x purchase price of winning trade x winning profit rate / (principal x elapsed days ÷ number of days of winning trade turnover of principal ÷ purchase amount per winning trade) + (loss rate x purchase of losing trade) Price x Loss loss rate / (Principal x Elapsed days ÷ Number of lost trade turnover days of principal ÷ Purchase amount per losing trade))} x Principal x Elapsed days ÷ Principal turnover days ÷ Purchase per purchase Price [Calculation method 2]
Total profit / loss = {(win rate x purchase price of winning trade x winning profit rate / number of wins) + (loss rate x purchase price of losing trade x losing loss rate / number of losses)} x principal x elapsed days ÷ rotation of principal Number of days ÷ Purchase price per purchase [Calculation method 3]
Total profit / loss = {(Win rate x Win profit / Number of wins) + (Loss rate x Loss loss / Number of losses)} x Principal x Number of elapsed days ÷ Number of days of principal rotation ÷ Purchase price per purchase [Calculation method 4]
Total profit / loss = {(win rate x winning profit per time) + (defeat rate x losing loss per time))} x principal x elapsed days ÷ number of days of principal turnover ÷ purchase price per time [calculation method 5]
Revenue amount per transaction x Principal x Number of elapsed days ÷ Number of days of principal rotation ÷ Purchase price per transaction = Total profit / loss [Calculation method 6]
Total profit / loss = Revenue amount per transaction x Principal x Number of elapsed days ÷ Number of rotation days of principal ÷ Purchase price per transaction [Calculation method 7]
Total profit / loss = amount of profit per transaction x number of transactions [Calculation method 8]
Total profit / loss = {(win rate x win profit per time) + (defeat rate x loss loss per time))} x number of trades As described above, calculate the total profit / loss and calculate each evaluation index. Therefore, multifaceted evaluation is possible.

here,
The number of rotation days of the principal = the number of elapsed days ÷ the number of rotations or the number of rotation days of the principal = the number of elapsed days ÷ principal × purchase price.

Here is an index that shows how many days it takes to make one revolution.
Principal Winning Trade Rotation Days = Elapsed Days ÷ Winning Trade Rotation Numbers or Principal Winning Trade Rotation Days = Elapsed Days ÷ Principal x Winning Trade Purchase Price Information generation unit 3021 loses the number of rotation days in the case of winning trades. By comparing with the number of rotation days in the case of trading, it is determined whether or not there is a difference between the two. The characteristics of a winning investor are that the winning profit margin is usually high and the number of turnover days tends to be longer than that of a losing trade, so it is an index to confirm it.

Purchase price per purchase = purchase price ÷ number of transactions.

The same applies to the case of the purchase price per winning trade = the winning trade purchase price ÷ the number of winning trades and the losing trade.

The above is the case of total profit / loss, and the total profit / loss ratio is total profit / loss / principal, which can be obtained by expressing the above formula by dividing by the principal.

In the case of total profit / loss during the AB period, investment products purchased before point A and held at point A need to be revalued at point A.

Further, if the total profit / loss in the AB period / the valuation amount at the time of A = the total profit / loss ratio in the AB period is defined, the total profit / loss ratio in each year becomes clear.

Furthermore, the same formula can be used not only for the total profit / loss level but also for the trading profit / loss level and the unrealized profit / loss level.

(Problems of conventional technology)
For example, in the past, when evaluating the total profit / loss level, the winning trade and the losing trade were not separately evaluated, and usually, the transition of the valuation amount (= principal + total profit / loss) or The rate of increase / decrease in the valuation amount is the target of evaluation. However, with this, it was very difficult to understand what was wrong and what was good, but rather I did not know.

By dividing the total profit and loss into winning trades and losing trades, various evaluations are possible. However, at the trading profit / loss level, the winning trade and the losing trade are evaluated separately in the first form, but in the formula, it is a function of the calculation method 2. Here, it is presented that it can be calculated by a wider range of methods.

(Effect of evaluation of transaction data)
The details differ depending on which of the above seven levels is used to separate the winning trade and the losing trade at the total profit / loss level. These formulas are used to decompose the total profit and loss and the total profit and loss ratio. By calculating various evaluation indexes obtained there, it becomes possible to evaluate the transaction data. Of course, the type of transaction data is defined by the aggregated trading data and the component trading data. For example, it is possible to evaluate transaction data (trading data in a narrow sense) defined by trading data subject to aggregation by period, trading data targeted for investment, etc. from various angles.

(Effect of evaluation of transaction data)
By systematically calculating the evaluation index of transaction data as described above, various evaluation indexes can be calculated and the transaction data can be evaluated by combining the profit and loss level and the evaluation method based on the formula. It is possible to calculate an evaluation index for various transaction data extracted by the aggregated trading data and the component trading data at various profit and loss levels and with various formulas. The effect of evaluation using the calculated evaluation index becomes remarkable, for example, by period or investment target, and brings about an unprecedented effect. For example, it is possible to evaluate that a person with a high result in 2020 has a high rate of return on winning, and the average number of days a winning trade is held is 3 months, but the number of days a losing trade is held is 1 week. Become.

[Specific example of evaluation of transaction data 1]
By evaluating the total profit / loss level of the trading data subject to aggregation by period, the factors that won or lost by year can be clarified.

[Specific example 2 of evaluation of transaction data]
By evaluating the trading profit / loss level of the trading data to be aggregated by investment target, it is possible to grasp the winning and losing patterns by comparing the winning trade and the losing trade of the relevant issue, and increase the probability of winning. Will be able to.

[Specific example 3 of evaluation of transaction data]
When evaluating the transaction data of Investor A, the winning trade and the losing trade are evaluated separately at the total profit / loss level, and the winning trade and the losing trade are further divided at the trading profit / loss level and the unrealized profit / loss level. It is possible to accurately grasp the current situation and the past situation, and it is possible to make a more detailed breakdown as well as the overall picture at the total profit and loss level.

[Specific example 4 of evaluation of transaction data]
It is possible to evaluate the results of stocks in FY2020 and FY2019 from various angles such as comparison of winning percentages and losing trades.

(Relationship between transaction data evaluation and profit / loss level evaluation index)
The evaluation of transaction data is to express profit or loss or profit / loss ratio as a function, and to express that the profit or loss, which is the purpose of transaction data, increases or decreases due to various factors.

The target profit / loss is classified into first-level total profit / loss, second-level trading profit / loss, unrealized profit / loss, third-level winning profit, losing loss, unrealized profit, and unrealized loss.

The meaning of the first-level winning trade is a concept that includes counter-trading completed trading data and non-counter-trading data, and the winning rate also includes both.

On the other hand, the meaning of the second level is that the counter-trading and trading data is evaluated as the counter-trading and trading data, and the non-counter-trading data is regarded as the non-counter-trading data, and the winning trade and the losing trade are evaluated separately. The former is the result of the past, and the latter is the current progress.

Once the profit / loss level trading data is determined, the target profit / loss level trading data is determined, and the transaction data can be evaluated.

(Significance of evaluation of technical index values)
The information generation unit 3021 adds a technical index value as an evaluation index. This makes it possible to evaluate the trading data from the aspect of technical index values. Since it is possible to manage the technical index value at the time of purchase, the technical index value at the time of sale, and the technical index value at the time of possession, it is possible to manage the technical index value at the time of success and the technical index value at the time of failure, and the aspect of the technical index value. Enables trading trends and trading evaluations.

(Problems of conventional technology)
Trading and technical index values are managed separately, and the trading tendency seen from the technical index side of Investor A, the trading tendency seen from the technical index side of Investor B, investment performance, etc. Centralized management has never been possible.

(Effect of evaluation of technical index value)
The information generation unit 3021 adds a technical index value to various evaluation indexes of trading data. As a result, the technical index value of the investment target at the time of purchase and the technical index value of the investment target at the time of sale are managed together in the trading history data. With regard to the investment target products that are in possession, the technical index values according to the market price will be managed according to the daily changes in the market price, and can always be managed. This makes it possible to accurately display and notify danger signals and the like.

(Effect of evaluation of technical index values)
It is possible to manage the technical index value along with the stock price, number of shares, brand, date, etc. at the time of purchase, and it is also possible to manage at the time of sale or holding.

It will be possible to easily manage the transition of the technical index value from the purchase to the sale of the successful trade of the excellent performer, the tendency of the technical index at the time of purchase of the excellent performer, the tendency of the technical index at the time of sale, etc. ..

(Specific example of evaluation of technical index value)
Investor A, who buys and sells frequently, has an average RSI of 80% at the time of purchase, an average RSI of 75% at the time of sale, a win rate of 50%, and a winning profit rate. It is possible to show in detail the state where assets are decreasing with a loss rate of 4% and a loss rate of -5% by adding not only the evaluation index obtained from the trading data but also the technical index value.

(Definition of evaluation of performance data)
Performance data of the investment target (company) is added as an evaluation index of trading data. This makes it possible to evaluate the trading data from the perspective of the performance data of the investment target. Since it is possible to manage performance data at the time of purchase, performance data at the time of sale, and performance data at the time of holding, it is possible to manage performance data at the time of success and performance data at the time of failure. Allows evaluation of.

(Problems of conventional technology)
The trading and investment target performance data are managed separately, and the buying and selling tendency from the perspective of the investment target performance data of Investor A and the trading tendency from the perspective of the investment target performance data of Investor B. Until now, it has been impossible to centrally manage investment performance and other factors.

(Effect of evaluation of performance data)
Since the performance data of the investment target is included in the various evaluation indexes of the trading data, the performance data of the investment target at the time of purchase and the performance data of the investment target at the time of sale are included in the trading history data. It will be managed. For the investment target products that are in possession, the performance data of the investment target will be managed and can always be managed. This makes it possible to accurately display and notify danger signals and the like.

(Effect of evaluation of performance data)
It is possible to manage the performance data of the investment target together with the stock price, the number of shares, the brand, the date, etc. at the time of purchase, and it is also possible to manage the performance data of the investment target at the time of sale or holding.

The transition of the performance data of the investment target from the purchase to the sale of the successful trade of the excellent performer, the tendency of the performance data of the investment target at the time of purchase of the excellent performer, the tendency of the performance data of the investment target at the time of sale, etc. Will be easy to manage.

(Specific example of evaluation of performance data)
It is said that the buying timing of excellent performers is often the first upward revision of the forecast value in the performance data of the investment target, and the selling timing of the excellent performer is the first downward revision of the forecast value in the performance data of the investment target. It will be understood, and the performance data of the investment target will be included along with the transaction data such as the buy price, the number of purchases, and the date of buying and selling. By linking the performance data of the investment target and the transaction data, it is possible to discover the habits of investors and the success patterns of the investment target.

(Definition of evaluation of other investment target data)
By adding trading data of other investment targets as an evaluation index, it is possible to evaluate the trading data from the aspect of trading data of other investment targets.

Since it is possible to manage trading data of other investment targets at the time of purchase, trading data of other investment targets at the time of sale, and trading data of other investment targets at the time of holding, trading data of other investment targets at the time of success and failure. It becomes possible to manage trading data of other investment targets at the time, and it is possible to evaluate trading trends and trading from the aspect of trading data of other investment targets.

(Problems of conventional technology)
Trends in other investment targets usually need to be managed by yourself, but it is very difficult to understand how other investment targets are performing compared to the investment targets you purchased. It becomes complicated. Most of the cases are unable to manage other investment targets.

(Effect of evaluation of other investment target data)
At the time of purchase, it was possible to select other investment targets, and what kind of results would have been achieved if other investment targets had been selected is one of the important information.

For example, if one month has passed since the purchase of A stock on the first section of the Tokyo Stock Exchange, the average of all stocks on the same first section of the Tokyo Stock Exchange would have increased by 5%, but the A issue has increased by 10% and the top issue has. It is managed as if the B brand had a 30% increase.

(Effect of evaluation of other investment target data)
Recognizing that you have made better choices will allow you to take the following lessons, determine if they were better than average, compete for skill in stock selection, and manage.

(Specific examples of evaluation of other investment target data)
In the case where the price range of the investment product A for a certain period increased by 7% in 3 months, the average of the whole period increased by 5%, so the average is higher than the average, but the Z issue It greatly exceeded the 50% increase, and was ranked 500th among the 2100 stocks on the First Section of the Tokyo Stock Exchange. The addition of this kind of information adds a deeper, more comparative evaluation than just a 7% increase.

(Definition of valuation of other investor data)
By adding the trading data of other investors as an evaluation index, it is possible to evaluate the trading data from the viewpoint of comparison with the trading data of other investors.

Since it is possible to manage the trading data of other investors at the time of purchase, the trading data of other investors at the time of sale, and the trading data of other investors at the time of holding, the trading data of other investors at the time of success and the trading data at the time of failure It is possible to manage trading data of other investors, and to compare trading data of other investors with trading trends and evaluation of trading.

(Problems of conventional technology)
The trends of other investors are usually unknown, but it is difficult to understand what other investors are doing compared to buying and selling by themselves, but if you can refer to it, , Very meaningful information. In the past, it was not possible to grasp what kind of investment behavior other investors are doing when they are doing investment behavior.

(Effect of evaluation of other investor data)
At the time of purchasing A stock, there was an investor who also acted to purchase A stock in the same way, and how that investor subsequently sold is one of the very important information. It is one.

For example, if one month has passed since the purchase of the A brand on the first section of the Tokyo Stock Exchange, 100 people purchased it at the same time under the data management, but one month later, half of the holders and half of them have already purchased. You can get information that you sold it. Information such as the average selling price and what the holder will do in the future is very important information.

In order to understand this, it is necessary to extract trading data with the same brand and purchase date. It would be easy if we could do that, but until now we have never provided such information.

(Effect of evaluation of other investor data)
For the investor, the information on the purchased stock is more important than the information on other stocks. In particular, what actions the investors who bought the same stock at the same time took after that is very important, and it is useful information for deciding whether to sell or keep holding. .. This is especially true if you know the subsequent buying and selling behavior of the excellent performers.

(Specific examples of evaluation of other investor data)
From a large number of trading data, trading data with the same brand and purchase date is extracted, and the holding status and trading status of the trading data, trading status by investor type, average profit / loss ratio, average holding period, average purchase quantity, Knowing the maximum price range, etc. will be very useful information for the purchaser of the brand. By comparing whether the price range was larger than that of other investors with the same purchase date and brand, how long the holding period was, etc., the skill of buying and selling was better than that of other investors. Can be evaluated. A deeper evaluation is possible compared to a simple profit / loss ratio.

(New method of AI machine learning evaluation process)
The AI machine learning evaluation process is performed through the following process.

The second step is the process of creating trading data to be aggregated. The third step is the creation of component trading data (optional). The fourth step is the process of creating the profit / loss level evaluation index (the target evaluation index is calculated by the information processing system by the three methods). Up to this third stage, the target profit and loss and the target trading data are determined. Extraction conditions, classification conditions, and aggregation conditions for trading data are also determined.

The fifth step is to calculate the evaluation index, which is a component of the target profit / loss (total profit / loss, trading profit / loss, etc.) determined in the third stage, by the information processing system (optional). The fourth stage can be included in the third stage or can be another stage.

Up to this fourth stage, the target profit and loss, the target trading data (data structure created under various conditions), and the evaluation index that is a variable are determined.

In the sixth step, in the evaluation process, based on the evaluation index calculated by the information processing system, machine learning is performed and the evaluation method is used to find the optimum solution. (Evaluation step).

It is the display step of this evaluation that displays the evaluation that is the optimum solution in an appropriate display method. Examples include tables, pie charts, components, ranking displays, comparison displays, etc. (see FIG. 77).

(Issues in the AI evaluation process)
In the above-mentioned evaluation process, there is a problem that there are many options for making it easy for anyone to decide which trading data to use, which profit / loss to evaluate, and which evaluation index to use.

Taking one step further from the above evaluation process, in order to maximize the target profit and loss, evaluation is performed by adding the process of storing the evaluation index as a variable, the process of finding the optimum solution, and the process of displaying it. The process evolves into an evaluation process by AI learning using machine learning.

If you decide the target profit and loss using the trading data, learn which evaluation index should be improved to improve the evaluation, and learn the points that the evaluation is inferior to other trading data. go. By displaying the learned results, the AI evaluation process will allow AI to find the optimal solution.

(Action of AI evaluation process)
In addition to the above-mentioned evaluation process, once the target trading data and the target profit / loss are decided, in order to improve the target profit / loss and optimize it, optimize which evaluation index should be used. By learning whether to go and displaying the evaluation index to be changed and how to change the evaluation index, it is possible to make a transaction that approaches the optimum solution. To go.

(Significance of AI evaluation process)
In addition to the above-mentioned evaluation process, we will add a process to learn how profit and loss will change if the evaluation index is changed. A storage unit that stores it, an evaluation index that is a variable, a target profit / loss, target trading data (aggregation target trading data and component trading data extraction conditions and classification conditions, aggregation conditions), a learning unit, etc. There are methods, software, devices, database structures, and learning methods.

(Effect of AI evaluation process)
By adding the AI process in addition to the above-mentioned evaluation process, it is effective to perform machine learning on how to evaluate the target trading data as the optimum solution.

(Specific example of AI evaluation process)
(Specific example A)
For example, if you want to improve Mr. A's total profit and loss, create Mr. A's total profit and loss data, create total profit and loss level trading data (even if you have it in the previous process), and it is a component of total profit and loss. In order to optimize the total profit and loss of Mr. A with the evaluation index as a variable, we will learn which evaluation index should be improved and how to optimize it. If you aim for a winning rate, change the winning rate from the current 50% to 60%, and change the winning profit rate from the current 4% to 5%, the trading profit of 1 million yen will be 80% in one year. Increase with probability. For example, some patterns are displayed, and the target is a combination with a high probability and a large degree of change.

(Specific Example B)
For example, when it is desired to improve the trading profit / loss of the A stock, the trading profit / loss data of the A stock is collected by creating the trading data to be aggregated of the A stock and targeting the trading profit / loss level trading data. Trading profit / loss level of stock A Various evaluation indexes that affect trading data are calculated by the information processing system, and the influence of these various combinations on trading profit / loss is learned, and the holding period of stock A and the holding period Learn the trading profit margin, the trading profit ratio and average holding period of the person who has the highest trading profit, and learn the trends such as the purchase time and sale time of the person who has the lowest trading loss. One of the specific examples is to display that the purchase success rate is high when the person who has the highest trading profit of the A brand purchases it, and the sale success rate is high when it is sold. ..

(Specific Example C)
For Mr. A who buys and sells using Twitter, create component trading data for each reference medium of the aggregated trading data of all investors, and create total profit and loss level trading data (have it in the previous process). It is also possible), learn and remember which reference medium is what kind of result, and when buying and selling using Twitter, the winning profit rate tends to be low, the losing loss rate tends to be large, and it is difficult to achieve results. Learn and tell that buying and selling using the quarterly report has a high rate of return and is easier to achieve results than Twitter, and display which evaluation index should be improved by combining evaluation indexes Is an example.

(Specific Example D)
Create trading data by investment target based on stocks in the category of traders, stable growth stocks, and high-growth stocks, create total profit / loss level trading data, and learn the difference between each evaluation index. To go. After obtaining the learning results, if the A stock is a stock in the category of the trader stock, by displaying the information about the stock, what precautions should be taken when trying to purchase the A stock, the loss will increase. , Many people are greatly reducing their funds, etc. can be displayed.

(Specific example E)
Create aggregated trading data by investor of group A with high performance with Mr. A, create a total profit and loss table, learn various evaluation indexes of Mr. A, learn various evaluation indexes of group A, When evaluating the holding status, if it is Group A, it is possible to display such as changing the holding status in this way.

(Definition of evaluation method)
FIG. 31 shows the difference in the overall picture of each step of the old method and the new method. In the new method, the information generation unit 3021 executes the evaluation step after completing the step of creating the aggregated trading data. do.

FIG. 32 is a flowchart showing a method of evaluating a trading status and a holding status according to the present embodiment. There are the following five methods for evaluating the aggregation target using the profit / loss level evaluation index calculated by the information processing system based on the aggregation target trading data.
(1) Trading status and holding status evaluation (2) Trading status evaluation (3) Holding status evaluation (4) Linked holding status evaluation (5) Linked trading status and holding status evaluation These are all trading data subject to aggregation by period. It is also applicable to the evaluation in the above, the evaluation by the trading data to be aggregated by investment target, and the like.

(Old method of evaluation step)
The trading profit / loss according to the first embodiment is an example of an axis for evaluating where there is a problem in trading and what is good. The principal increase / decrease rate according to the first embodiment is an example of an evaluation axis for comprehensively evaluating and evaluating the trading status and the holding status.

As described in the first embodiment, the evaluation axis is used as a cut for evaluating the trading data. For example, the rate of return on winning is given as an example of the evaluation axis, and it is calculated by the information processing system from the winning data that classifies the traded data by "profit amount per win ÷ trading value per win". .. These evaluation indexes are calculated by the formula "total profit amount / number of wins".

On the other hand, in the present embodiment, the information processing system calculates the trading profit / loss level from the trading data including the trading profit / loss ratio, the trading profit / loss amount per transaction, etc., which is extracted (or classified, aggregated, processed).

FIG. 33 is a diagram showing an example of extracting (or classifying, tabulating, and processing) trading profit / loss level trading data according to the present embodiment (processing of trading profit / loss level trading data in FIG. 26). As can be seen by comparing FIG. 26 with FIG. 33, the period-specific aggregation target trading data created in FIG. 26 can be used as it is.

According to this method, as shown in FIG. 33, the evaluation by period can be simplified by going through the process of extracting (or classifying, totaling, processing) the trading data to be aggregated by period in FIG. 26. Aggregation by investment target After going through the process of extracting (or classifying, aggregating, and processing) trading data, there is a special effect that evaluation by investment target can be simplified. In the old method, for example, it is difficult to calculate by the information processing system for each period of time A and time B. With the new method, all data can be managed in a database, so individual and total values can be freely processed and used, which has a special effect.

(Issues in the evaluation step)
The problem with the old method is that it is not possible to make detailed evaluations such as evaluating by period, evaluating by investment target, and evaluating the buying and selling of stocks of Investor A in 2019. The evaluation process follows the following process. The trading data to be worked is determined through the process of the second step (or the first step) of creating the trading data to be aggregated and the component trading data. In the 4th and 5th steps, which evaluation index is targeted is decided. It is possible to evaluate the target (sixth step) using the trading data of the fixed work target and the target evaluation index. By displaying the evaluations made by an appropriate display method, the evaluations can be understood at a glance. It is not just a list of numbers, it is displayed in a suitable display method.

The evaluation step refers to a step (see FIG. 77) of performing evaluation in the evaluation process.

(Action of evaluation step)
The information generation unit 3021 calculates the profit / loss level evaluation index by converting the trading data into the trading data to be aggregated and further processing and extracting it into the profit / loss level trading data, and evaluates the aggregation target with the evaluation index. When the trading data is used as the trading data to be aggregated, the purpose and the aggregation target are decided, and the trading data is created according to the purpose by processing and extracting the profit / loss level trading data, so that the evaluation index can be easily processed. Calculated by the system.

Of the trading data, what kind of trading data is targeted is the process of the first stage and the second stage. The profit / loss level at which the trading data is evaluated is the third stage, which determines the profit / loss at which the trading data is evaluated. Further, by calculating the evaluation index constituting the profit / loss by the information processing system, the evaluation index that influences the result of the profit / loss is calculated by the information processing system. With reference to this evaluation index calculated by the information processing system, the trading status and holding status of the evaluation target will be evaluated. This step is an evaluation step. These evaluations are displayed (display step) by an appropriate display method. By this series of flow, the target evaluation target, the target profit / loss, and the evaluation index related to it are determined, and the evaluation index of the target profit / loss of the evaluation target can be used to evaluate and display the system.

(Effect of evaluation step)
By extracting (or classifying, aggregating, processing) trading data by period, investment target, investor, and profit / loss level, trading data according to the purpose is extracted (or classified, aggregated, processed) and evaluated. Can be easily calculated by the information processing system, and can be displayed as a list, which contributes to the evaluation of the data to be aggregated. For example, in order to evaluate the trading profit / loss of Mr. A in 2019, the trading data to be aggregated by Mr. A is created, and the year word component trading data of Mr. A is created with the year as a component. As a result, Mr. A's trading data for FY2018, FY2019, and FY2020 is created (steps 2 to 3). In order to evaluate the trading profit / loss, trading data below the trading profit / loss level is created for each of Mr. A's FY2018, FY2019, and FY2020. Among them, by creating the trading profit / loss level trading data for FY2019, the trading profit / loss amount (total value) of Mr. A in FY2019 is determined. For example, if it is 1 million yen, this 1 million yen will be the amount of money earned by various trading in 2019. The target of trading profit of 1 million yen for Mr. A in 2019 is set (steps 2 to 4). ) How do you evaluate it and lead to improvement? Is the reason why he earned this 1 million yen at the next stage, and he bought and sold the principal (valuation amount at the beginning of 2019), the valuation amount at the end of 2020, the number of transactions, the winning rate, the winning profit and the losing loss. Various evaluation indexes, which are decomposition elements, components, and related elements that cause profits, are calculated by the information processing system (fifth step). Using these evaluation indexes calculated by the information processing system, the trading status of Mr. A in 2019 is evaluated (the evaluation step in the sixth step), and the trading profit of Mr. A in 2019 of 1 million yen is 2019. Since the components of the issue (evaluation index such as the trading profit of 100,000 yen for A brand) can be calculated from the trading data of the trading profit of Mr. A, the A brand out of the trading profit of 1 million yen can be calculated. Evaluation indexes such as 100,000 yen for B and 200,000 yen for B brand can be calculated by the information processing system, and the evaluation has the effect of clarifying the trading situation.
Since the trading profit of 1 million yen is made by buying and selling 10 times, the winning rate is 60%, the winning profit is 1.3 million yen, and the losing loss is 300,000 yen. With these evaluation indexes, it becomes possible to evaluate the trading situation of Mr. A's trading profit of 1 million yen in 2019 (the step). At this time, these numbers may be listed, or these numbers and text may be combined and conveyed as a sentence.

(Specific example of evaluation step)
By stepping through the evaluation steps, for example, the trading results of Mr. A's stock as a whole in 2019, the current holding status evaluation of company S's stock (how much the average purchase is, etc.), will increase significantly in 2019. It is possible to make various evaluations such as whether all the stocks A that have been made are profitable, lost, and what about the people who have them now.

For example, in order to evaluate the trading profit / loss of A brand in 2020, create the trading data to be aggregated for A issue (Mr. A, B, C, etc. are grouped together and only the trading data for A issue is evaluated. Is extracted), and the year component trading data of issue A is created with the year as a component. As a result, trading data for the A issue in FY2018, FY2019, and FY2020 is created (steps 2 to 4). In order to evaluate trading profit / loss, trading data below the trading profit / loss level is created for each of the A issue in FY2018, FY2019, and FY2020. Among them, the trading profit / loss level of 2020 is created (it is possible to have it in the previous process), and the trading profit / loss amount (total value) of the A issue in 2020 is determined. For example, if it is 50 million yen, this 50 million yen will be the amount of money earned from various trading of A brand in 2020.

The trading profit of 50 million yen of the A brand in 2020 and the evaluation target are decided (steps 2 to 5) How to evaluate it? Is the reason why this 50 million yen was earned in the next stage, and it is the decomposition element, component, and related element that are the components that generate the trading profit such as the number of transactions, the winning rate, the winning profit and the losing loss. Various evaluation indexes are calculated by the information processing system (fifth step). It is a process of evaluating the trading status of the A brand in 2020 (the step) using these evaluation indexes calculated by the information processing system.
In this step, it is a step of bridging which evaluation index is used and what kind of expression is used. In order to accurately express the trading profit and loss of issue A in 2019, the step of deciding which evaluation index to use and what expression to use is important, but this is done in the 4th to 6th stages. How to make the expression easy for the user is done in this process.

It may be expressed in sentences, in a list of numbers, in a graph such as a pie chart, a bar graph, or a chart, or in a table.

Charts are suitable for trading profits of stocks. Aggregation by investment target The chart expression is accurate when extracting or classifying issues from trading data or component trading data.

It is said that the price movement of the A brand in 2020 was expressed on the stock price chart, the buying price buying time was plotted, the selling price selling time was plotted (expressed by dots and stars, etc.), and the average was bought here and sold here. The display can be expressed visually.

Further, for example, if an investor is used as a component based on the above-mentioned 2020 A issue trading data, the 2020 A issue is divided into A's trading data and B's trading data. By using profit and loss as trading profit and loss and using the number of trades as an evaluation index, it is effective to make it clear at a glance who earned the most and how.

A pie chart is suitable for clearly displaying who earned the trading profit of stock A in 2020, and the person who earned the most is each evaluation index (number of trading, number of days held, winning profit rate and losing loss rate). Etc.) is made into a hexagon, and the process of the sixth stage is to select an appropriate expression method such as which number is better than the average.

The target trading data is determined by the combination of the trading data to be aggregated and the component trading data. The target profit and loss is determined in the fourth step. In the fifth step, the evaluation index that affects the profit and loss is calculated by the information processing system. The sixth step is to perform various evaluations using the evaluation index calculated by the information processing system. The display step of the sixth step is how to display the evaluation.

(Definition of evaluation of trading status and holding status)
The step of evaluating the trading status and the holding status on the leftmost side of FIG. 32 is the simplest because it is a step of evaluating the trading status and the holding status without separating them. That is, as shown at the top of FIG. 34, the step refers to an evaluation that does not separate trading and holding. FIG. 34 is a diagram illustrating how the holding status evaluation and the trading status evaluation according to the present embodiment are separated.

Based on the aggregated trading data created in the aggregated trading data creation step, the profit / loss level trading data is created by the information processing system (it may be held in the previous process), and the calculation step of the profit / loss level evaluation index is performed. The process of calculating an evaluation index and evaluating the holding status and trading status using the evaluation index is defined as holding status and trading status evaluation.

(Issues for evaluation of trading status and holding status)
In order to evaluate the target of aggregation based on the trading data to be aggregated, the profit / loss level trading data is extracted and created, the profit / loss level evaluation index is calculated, and the trading of the aggregation target is used. Evaluate the status and holding status.

In the old method, the evaluation index is calculated from the numerical data. In the new method, the evaluation index is calculated based on the processed trading data. In the new method, for example, items such as the winning profit rate, the winning profit amount, and the trading period are added to the winning profit trading data, so that the evaluation index can be easily calculated.

(Effect of evaluation of trading status and holding status)
The information generation unit 3021 extracts and processes the profit / loss level trading data based on the created trading data to be aggregated through the step of creating the trading data to be aggregated, and goes through the step of calculating the profit / loss level evaluation index. An evaluation index is calculated, and the trading status and holding status are evaluated using the evaluation index.

(Effect of evaluation of trading status and holding status)
By evaluating the holding status and trading status of the aggregation target, it is possible to evaluate the aggregation target.

(Definition of trading status evaluation)
The second step of evaluating the trading situation from the left in FIG. 32 will be described. Based on the trading data to be aggregated created in the process of creating trading data to be aggregated, the trading data below the trading profit / loss level is extracted and created, and the evaluation index is calculated through the calculation step of the profit / loss level evaluation index. Evaluating the trading status using the evaluation index is defined as trading status evaluation.

(Old method)
As shown in the first embodiment, the advice generation unit 321 calculates an evaluation index such as a total trading profit / loss from the trading data.

(Issues of trading status evaluation)
The second flow from the left in FIG. 32 is a diagram showing a procedure for evaluating the trading status according to the present embodiment. The information generation unit 3021 evaluates the status of the aggregation target using the calculated evaluation index.

The counter-trading has been done in the past, and the trading status is the final trading data. Various valuation gains and losses are calculated based on the confirmed trading data, and the trading status of the aggregation target is evaluated using the evaluation index. First of all, by evaluating the trading situation, it is possible to grasp the past results properly. And since past achievements create the current holding situation, it is possible to evaluate in chronological order by evaluating separately.

(Means for evaluating trading status)
As shown in the second flow from the left in FIG. 32, the information generation unit 3021 extracts and creates trading data below the trading profit / loss level based on the trading data to be aggregated, and calculates a profit / loss level evaluation index. After that, an evaluation index is calculated, and the trading status is evaluated using the evaluation index.

That is, the information generation unit 3021 of the server 30 acquires the trading data of the investment product, creates the trading data to be aggregated by summarizing the trading data for each standard, and uses the trading data to be aggregated to obtain the trading profit / loss related to the determined profit / loss. Create level trading data (even if you have it in the previous process), calculate the trading profit / loss level evaluation index for evaluating the trading profit / loss from the trading profit / loss level trading data, and use the trading profit / loss level evaluation index. Generate information about the valuation of trading profits and losses of investment products.

(Effect of evaluation of trading status)
By evaluating the buying and selling status separately from the holding status, the evaluation can be divided into the evaluation by holding and the evaluation by buying and selling, and the evaluation by narrowing down the target becomes possible.

(Specific example of trading status evaluation)
Mr. A's trading status evaluation in 2019, stock trading status evaluation in August 2019, virtual currency trading status evaluation, ETF trading status evaluation by individual investors, investment trust trading status in 2019 by individual investors It is possible to evaluate the trading status of various targets according to the creation of trading data to be aggregated, such as evaluation. This evaluation has the effect of giving a detailed understanding of the trading situation that is different from the actual price movement. Furthermore, it is possible to determine the actual state of useless revolving trading and whether or not the trading is for a valid reason.

(Definition of holding status evaluation)
The third step of the possession status evaluation from the left in FIG. 32 will be described. Based on the trading data to be aggregated, the trading data below the unrealized profit / loss level is extracted and processed, and the evaluation index is calculated through the calculation step of the profit / loss level evaluation index, and the holding status of the aggregation target is evaluated using the evaluation index. This is defined as the evaluation of the holding status of the trading data to be aggregated.

(Issues for evaluation of ownership status)
The holding status without counter-trading consists of unconfirmed trading data currently in progress. Various valuation gains and losses are calculated based on this undetermined trading data, and the holding status of the aggregated object is evaluated using the valuation index. Trading data that is not counter-trading is currently bound funds. The method of evaluation differs in many ways from the funds that are bought and sold in the opposite direction, and it is necessary to evaluate them separately.

(Means for evaluating ownership status)
The information generation unit 3021 is created by extracting and processing trading data below the trading profit / loss level based on the trading data to be aggregated created in the step of creating the trading data to be aggregated, and undergoes the calculation step of the profit / loss level evaluation index. An evaluation index is calculated and the holding status of the aggregation target is evaluated using the evaluation index.

That is, the information generation unit 3021 of the server 30 acquires the trading data of the investment product, creates the aggregated trading data that aggregates the trading data for each standard, and uses the aggregated trading data to include the undetermined profit and loss. Create profit / loss level trading data (even if you have it in the previous process), calculate the unrealized profit / loss level evaluation index for evaluating unrealized profit / loss from the unrealized profit / loss level trading data, and use the unrealized profit / loss level evaluation index. , Generate information on the valuation of unrealized gains and losses on investment products.

(Effect of holding status evaluation)
By evaluating the holding status separately from the trading status, the evaluation can be divided into the evaluation by holding and the evaluation by buying and selling, and the evaluation with a narrower target becomes possible.

(Specific example of holding status evaluation)
As shown in the upper figure of FIG. 34, the information generation unit 3021 buys and sells as shown in the central figure when evaluating profit and loss data in which the principal is 500,000 yen and the current valuation amount has increased to 2 million yen. The evaluation of profit / loss of 500,000 yen and the evaluation of unrealized profit / loss of 1 million yen are performed separately.

Trading profits and losses are fixed funds, and unrealized gains and losses are ongoing funds that fluctuate daily.

On the contrary, as shown in the lower figure of FIG. 34, even if the information generation unit 3021 also increases from 500,000 yen to 2 million yen, the trading profit / loss is 1 million yen and the holding profit / loss is 500,000 yen. , The meanings of the central figure and the figure below are different.

The trading status evaluation evaluates the trading profit and loss, and the holding status evaluation evaluates the unrealized profit and loss. It becomes clearer by including the concept of unrealized profit and loss formation funds as an intermediary. Hereinafter, specific examples of unrealized asset formation funds will be shown.

(Meaning based on "valuation at the start (or principal) + trading profit / loss-cash" = unrealized profit / loss formation fund)
In FIG. 32, the third step from the left in the holding status evaluation is "valuation at the start (or principal) + trading profit / loss-evaluate cash".

The significance of using the "starting evaluation amount (or principal) + trading profit / loss-cash" that appears in the linked evaluation as the standard is to process the funds that form unrealized profit / loss (unrealized profit / loss formation funds). It is done for the purpose of calculating by the system.

The example in the center and below of FIG. 34 show a simple case that does not include cash. The central figure shows the case of unrealized profit / loss formation fund of 1 million yen. The figure below shows the case of unrealized profit / loss formation fund of 1.5 million yen. The central figure has a higher evaluation of the current unrealized gain formation. This is clear because we are comparing the unrealized gain formation fund with the current valuation amount.

But what about cases that include cash?

FIG. 35 is a diagram showing the relationship between trading profit / loss and unrealized profit / loss (including cash) according to the present embodiment. FIG. 35 shows the same result that 500,000 yen became 2 million yen. However, FIG. 34 shows a case where the unrealized gain formation fund of 1 million yen is used. The central figure of FIG. 35 shows a case where the unrealized gain formation fund is 500,000 yen. In the former, 1 million yen becomes 2 million yen (double), and in the latter, 500,000 yen forms 1.5 million yen (triple), so the latter is superior in unrealized gain formation performance. I understand.

The latter was able to form the same unrealized gains despite leaving cash. Therefore, a model that includes principal, trading profit and loss, and cash is more suitable for valuing unrealized gains and losses, and correct valuation is possible.

Here, the principal can also be replaced with the valuation amount at time A. The principal will be the principal (original resource) that started investment from the cash on hand, but if the evaluation period is different from the time A, the starting point will be the valuation amount at the time A.

(Unrealized gain / loss formation fund and unrealized gain / loss in the case of trading data by period)
Unrealized gains / losses are an important factor in assessing holdings. FIG. 36 is a diagram illustrating a breakdown of the valuation amount of the profit and loss trading data for each period and the opportunity loss according to the present embodiment.

In the case of trading data by period, the unrealized profit / loss formation fund of 6.05 million yen is the fund that has been held since the time A (unrealized gain formation fund A 3.93 million yen) and the fund that was purchased during the AB period and has been held at the time B. It is divided into funds (unrealized profit formation fund B2.12 million yen).

The unrealized gain / loss is generated from the unrealized gain formation fund A and the unrealized gain formation fund B in FIG.

The funds that have been held since the time A are further made up of unrealized gains and losses that existed before the time A (6.71 million yen-3.93 million yen = 2.78 million yen in FIG. 36). Therefore, the current unrealized gains / losses are the unrealized gains / losses from before point A (2.78 million yen in Fig. 36) and the unrealized gains / losses after point A (2.62 million yen in Fig. 36), and the unrealized gains / losses purchased during the AB period and at point B. It can be divided into three categories: the unrealized gains / losses (650,000 yen in Fig. 36).

By evaluating the unrealized profit / loss formation funds that have been formed for each period, it is possible to make an evaluation for each period, so that a more precise evaluation model can be constructed.

The trading profit and loss has already been evaluated by the trading status evaluation, and it is the past data. On the other hand, unrealized gains / losses as an investment result of unrealized gains / losses (increased / decreased due to trading gains / losses) are funds that have not yet been determined and change daily.

Cash and unrealized gains / losses formation funds need to be evaluated separately from unrealized gains / losses. Cash is a product that does not generate profit or loss, and unrealized profit or loss is invested in products that generate profit or loss, so a separate evaluation is required. Unrealized P / L Level Trading data will be valued excluding cash, while a valuation process for keeping cash is required.

(Calculation of cash evaluation index (cash level evaluation index))
Cash does not generate profit or loss. That is why cash is valued by introducing the concept of lost opportunity. Opportunity loss represents a fictitious benefit that could not be gained by not making a decision. Opportunity loss is calculated by the information processing system by multiplying cash by the profit / loss ratio.

FIG. 36 is a diagram showing an example of a table of valuation amount and opportunity loss of profit / loss trading data for each period according to the present embodiment.

As shown in Fig. 36, cash of 10.69 million yen may double if it is used for purchase funds (because of unrealized profit / loss formation funds of 6.05 million yen, unrealized gain of 6.05 million yen, and valuation of 12.1 million yen). It means that there was. Calculate 10.69 million yen (= 10.69 million yen x 100%) as an opportunity loss. It would be an opportunity loss that would have been an unrealized gain if the investment had been made without leaving cash. These are information that should be comprehensively considered in the holding status evaluation.

How to evaluate this unrealized gain formation fund is the first important step. In other words, it is the process of how to evaluate the investment product you are currently purchasing. To put it plainly, the process is how to evaluate the purchased brand. This is referred to as the valuation process for profit and loss picture formation funds. What kind of information is associated with the investment products that you own in the information processing system? Owned investment products = purchased products. This includes the date of purchase, the brand purchased, the price purchased, and if entered in the input step, the reference medium at the time of purchase (quarterly report, Twitter, etc.), technical index value, etc. Corporate performance information, event information, brand information, brand news, etc. are linked (linked in the step of creating trading data to be aggregated). Furthermore, since this information is linked even after purchase (because not only the purchase date but also the date and the technical index value are related, the time series information is stored in a separate table), the holding status is displayed. There are procedures in place to use all of this information when making an evaluation. Therefore, this evaluation of the holding status is divided into a process of evaluating the unrealized profit and loss formation fund and a process of evaluating the progress of the purchased product so far.

(Significance of unrealized profit / loss formation fund evaluation process)
It's a difficult word, but the point is the evaluation of purchased products and the evaluation of purchased brands. This includes evaluation of the purchased product itself and evaluation of the purchase time of the purchased product. The evaluation of the purchased product itself is how to evaluate whether the brand selection was correct, incorrect, or not. The latter is the process of assessing whether the purchase was timely.

(Problems of conventional technology)
There is not much concept to evaluate whether the selection of the purchased product was correct. I don't know how to evaluate it. There are 3900 Japanese stocks alone, and there are many options for stocks alone. Take the steps to select from them. You choose from a number of options, but if you don't evaluate whether this is wrong, you will make the same mistake again. That is why this evaluation process becomes important, and if it can be evaluated correctly, PDCA will turn around and optimization will be possible.

(Action of unrealized profit / loss formation fund valuation process)
First of all, as far as the selection of Japanese stocks is concerned, how should we evaluate whether the selection of 3900 stocks was correct? This is possible with the information processing system. This is because the data of the purchased product at the time of purchase and various time-series data are linked, and the various information on the day of purchase changes as the date changes and the stock price fluctuates, but the stock price and technical indicators after that. This is because prices, stock news, corporate performance, etc. can be tracked in chronological order. Moreover, this is the same for other brands. In other words, it is a mechanism to understand how all 3900 brands have changed since the time of purchase.

(Effect of unrealized profit / loss formation fund evaluation process)
If the information is extracted for the sake of clarity, the chart shows the history of the A brand at the time of purchase. This is usually common information. At the same time, behind the scenes, there is stock price information of 3900 stocks, and information from the time of purchase can be withdrawn. First of all, this mechanism is used to determine whether the selection of brand A was correct. And what was the rate of increase / decrease in the selection of purchased products during the period, what was the other stocks, what was the average, and not only the stock price but also the corporate performance is linked. Therefore, it is possible to trace changes in corporate performance after purchase. Behind the scenes, all 3900 brands are.

In other words, the evaluation of the selection of stocks held was the evaluation of the rate of increase / decrease in stock prices after purchase and the evaluation based on changes in the performance of the target company (whether it was the selection of stocks with an increasing profit or the selection of stocks with a decreasing profit). This means that if you link all the factors that determine the stock price with the time series data, all the factors will be linked. However, even if it becomes too complicated, it will be difficult to understand, so first we will evaluate the selection by comparing the stock price data, which is the simplest. If the rate of increase / decrease from purchase to the present is 2.5 times in 160 days, it is usually enough to be happy and satisfied. However, in this information processing system, it is a system that can evaluate whether the selection is really optimal, and in fact, the Z brand (160 days period rise / fall rate ranking first place) has brought the best result in the last 5 months. The price has tripled in (Brands), the price has increased by 10% on average during this period, and the selection of A stock was 5th among them. .. The stock selection verification chart (Fig. 103) is defined as the stock selection evaluation process (or stock selection verification chart) of the profit and loss formation fund, and the process of evaluating whether or not the time selection was correct is also defined. Purchase time evaluation process Defined as a verification chart of stock purchase time (Fig. 104). This purchase time evaluation is free with the right to choose the purchase time only during the period of 160 days. If this was a year ago, the situation would be very different, and the funds would be tied up by other stocks, so it can't be helped to expand this far. Since the funds were tied up to the A brand for the last 160 days, it was possible to leave it in cash and purchase the A brand at a better timing, so you have the freedom to choose when purchasing here. , This holding period is 160 days. If I bought it 160 days ago, it was 2.5 times, but if I staggered it a little more and 100 days ago, the profit was actually only 30%. This means that 160 days before the purchase was almost the best choice. As a result, there are two processes for valuing unrealized asset formation funds, a stock selection valuation process and a stock purchase time valuation process, and by evaluating each, whether the selection was correct and whether the purchase time was correct. It is the effect of the integrated processing by the information processing system that makes it possible to evaluate correctly. This is done for each stock held. This is because the stocks held for one year are purchased at different times, so it is correct to evaluate the stocks held for one year according to the rate of increase / decrease in that year. Both the average and the number one stock will change.

(Specific example of unrealized profit / loss formation fund evaluation process)
(Verification chart for stock selection (Fig. 103)
Explaining with reference to FIG. 103, it means that the answer of how much the A brand is in the purchase of the A brand on 9/10 comes out. There are various options to purchase on 9/10. There are 3900 stocks to choose from for Japanese stocks alone. It is an epoch-making tool that can verify whether the selection of the A brand from these many brands was right or wrong.

(Problems of conventional technology)
In the past, whether or not the brand you bought was the correct answer had to be judged by whether it was profitable or lossy. I didn't know how to evaluate it. There is a verification of how it is compared to the Nikkei average. However, there are many options for buying and selling individual stocks, and there are also options after purchase every day (there is the freedom to sell and switch immediately). What was important in determining whether the stock purchased was correct was how the other stocks were. Of course, it's a matter of choice. However, there is no system in the world to verify this. Why?

(Action of stock selection verification chart (Fig. 103))
It was just because it was difficult to derive from the huge amount of information. However, this can be easily done by utilizing the information processing system under certain rules. The procedure is to aggregate "extraction conditions: investment products = stocks, purchase date = 9/10, component trading data: by brand" in the trading data to be aggregated by investment target on 2/17. With this, the total for each stock purchased on 9/10 of the stock, which is the basic set, will be displayed. After that, if you let the information processing system calculate the evaluation index of the rate of increase / decrease comparing the stock price of 9/10 and the stock price of 2/17 which is the record date, the rate of increase / decrease of other stocks in the holding period can be quickly obtained. If the ranking comes out and the selection is other than the selection of the stock, you can really experience what the result was.

(Effect of verification chart of brand selection (Fig. 103))
This also has a great effect. Stock selection has long been a challenge for investors. At this time, it is easy to come up with the answer as to what is the best stock selection. Of course, possession is not the only choice. In the previous example, it is the 5th place in the choice of holding 160 days, but other investors sell, replace with other stocks, make profits there, and earn by buying and selling in 160 days. This is because there are a lot of people out there. Therefore, if you do not look at this stock selection verification chart from various angles, it is not straightforward to say that the information that big data such as trading data can be output is profound. Nevertheless, the invention relating to this selection can be said to be an epoch-making invention that breaks down that corner.

(Specific example of the stock selection verification chart (FIG. 103))
Even if you buy at the same time, stocks will have a huge investment gap. Then you can properly know how much it has opened, and if you make a failed choice, that will be clearly shown in the numbers, and there will be an incentive to improve. As PDCA starts to turn around, the impact on investors is immeasurable.

(Significance of the verification chart (Fig. 104) of the brand purchase time)
Explaining with reference to FIG. 104, it is a chart in which the stock price chart of the A stock contains information about the participants of the A stock. In particular, it is a chart that shows what kind of investment behavior other investors who purchased the A issue at the same time (09/10 in this case) took. The information processing system can identify 3,500 investors (that is, those who purchased the A brand on 09/10). Some users have sold the investor in a day, while others have held it for 160 days. A chart in which these can be seen at a glance is defined as a verification chart of the stock purchase time.

(Problems of conventional technology)
A typical stock chart has information about the stock, but not the people who buy or sell the stock. The only way to know this is to collect fragmentary information such as bulletin boards and personal blogs. We don't know the actual investment behavior. However, in the information processing system, the information of this brand and the trading information of the investor are linked, and since it has a structure that is organically linked to the trading data of the investor at the time of the purchase of the brand, A. It is an epoch-making technology that makes it possible to understand the subsequent investment behavior of those who purchased on 9/10 of the brand.

(Action of verification chart (Fig. 104) at the time of brand purchase)
In the information processing system, first, the extraction condition is set as "stock: A brand, purchase time: 9/10" in the trading data to be aggregated by investment target, and the components are aggregated by investor. Then, assuming that the profit / loss level trading data is the total profit / loss level trading data, a basic trading data set is created by the information processing system. If the evaluation indicators are the sale date, holding period, sale quantity, purchase quantity, and purchase price in the trading data set, the sale date and holding period for each investor aggregated by those who purchased the A issue on 9/10, The sale quantity, purchase quantity, and purchase price are calculated by the information processing system, and the purchase price, sale price, sale profit / loss, and trading data without a sale date become the trading data in possession, and the purchase of the investor in possession. The unrealized gain is calculated by the information processing system based on the amount, purchase quantity, purchase unit price, and market price of 2/17, and based on these evaluation indexes, the data of 3500 people who purchased the A brand on 9/10 is Of these, 250 have not yet sold and formed unrealized gains, and the remaining 3250 have sold, with the average selling price being 1250 yen, the most frequent selling price being 1050 yen, and the highest selling price being 2300 yen. The information processing system can be easily derived. Since Mr. Z, who is in the first place, can easily derive the information sold for 2600 yen by the information processing system, such a verification chart of the brand purchase time can be easily derived by the information processing system.

(Effect of verification chart of brand purchase time (Fig. 104))
Investors are wondering how other investors are buying and selling. Moreover, there is no way to know how the investors who bought the stocks they bought on the same day they bought them acted after that. In the information processing system, it is an epoch-making system to understand it, and for investors, it is a chart that can verify investment behavior.

(Specific example of verification chart of brand purchase time (Fig. 104))
In the information processing system, this can be done for all brands, the purchase time can be changed, and as an application, everyone is doing what they are doing with the brands that they have already sold and do not own. Of course, it can also be used. It can be used for all investment targets that can be grasped by the trading data to be aggregated by investment target, such as the entire stock and the entire virtual currency.

(Significance of stock investment trend charts of other investors (Fig. 105))
Explaining with FIG. 105, it means that the answer "How many of the people who purchased the A brand on 9/10" comes out. Assuming that the number of people who purchased the A brand on 9/10 is 3,500 processed by the information processing system, all the actions taken by the investors remain in the storage unit 33 in the information processing system. ing. Utilizing that information, the actual trading records of those who purchased the stock on 9/10 will be aggregated. That is why these numbers are calculated by the information processing system.

(Problems of conventional technology)
I am very curious about what kind of investment behavior people who bought the same brand as themselves on the same day have taken since then. However, with conventional technology, that is not very clear. This information is not available in the world.

(Action of Stock Investment Trend Chart of Other Investors (Fig. 105))
However, why can this number be calculated by the information processing system? First, the purchase date is 9/10, the purchase brand is A brand, and the basic data set comes out easily. However, it is necessary to make the components investors, and it is necessary to aggregate them. Also, the profit and loss level trading data will be the first level trading data. If this is instructed to the information processing system, the rest is easy. If ranked by the total profit / loss ratio, the information processing system will immediately calculate who is the 1st place and who is the 5th place. Since it is linked with the purchase date and the brand set, it is possible to put it on the chart. As I saw in the table set, once these conditions are memorized in the table set, the information processing system automatically calculates and memorizes this ranking every day. Naturally, the ranking will also change. This kind of visualization is necessary for investment to be successful. Of course, not only the A issue but all the dates of all the issues are possible.

(Effects of stock investment trend charts of other investors (Fig. 105))
It has a tremendous effect. For investors, they can see how people who behave the same as the investment behavior they choose have actually behaved, and examine what makes them different from successful ones. be able to. Indeed, it can be said that this is a technology that greatly advances the visualization of investment. Above all, the linkage between the trading data to be aggregated by investment target and the component trading data is important, and it is a service that cannot be realized without it, and all of these are services derived from the consistency of processing of the information processing system. ..

(Specific example of stock investment trend chart of other investors (Fig. 105))
Since it can be used on all purchase dates of all brands, it can be used in various ways. You can see what everyone is doing when their stocks go down. In particular, people who are good at it and always have good grades are targeted.

It would be very reliable to know how (see the grouping section) works.

(Definition of stock investment trend chart of other investors (Fig. 106))
It is a chart that shows how other investors have bought and sold the A stock during the holding period of the A stock for 160 days. Of the 12,000 people who have bought and sold A stock in 160 days in total, 80% of the 12,000 people can buy and sell, and they do not currently own it, so the average trading profit and loss The rate is 25% and so on.

(Problems of conventional technology)
The behavior of other investors during the holding period of the same stock is now completely hidden information. Because I am worried about how I buy and sell the stocks I own, I check on Twitter and bulletin boards, and I feel happy and sad. With this information system, it is possible to draw out the trends of other investors in every direction. This is one of them.

(Action of Stock Investment Trend Chart of Other Investors (Fig. 106))
First, the extraction condition is set to "stock = A brand, purchase date = 2020/9/10 to 2021/02/17" in the trading data to be aggregated by period, and the information processing system collects the trading data by component aggregated by investor. (Including automatic, administrator, and user input forms), the information processing system creates a basic trading data set with the total profit / loss level trading data. If the evaluation indicators are the sale date, holding period, sale quantity, purchase quantity, and purchase price in the trading data set, it is aggregated by those who purchased stock A between 2020/9/10 and 2021/2/17. The sale date, holding period, sale quantity, purchase quantity, and purchase price for each investor are calculated from the information processing system, and the purchase price, sale price, sale profit / loss, and trading data without a sale date are currently held. It becomes data, and the unrealized gain is calculated by the information processing system based on the purchase price, purchase quantity, purchase unit price, and market price of 2021/2/17 of the investor in possession. Based on these evaluation indicators, the data of 12,000 users who purchased the A brand from 9/10 to 2/17 are available, of which 1500 have not sold yet, forming unrealized gains, and the remaining 10500. A person sells, and the trend is that the average purchase price is 1550 yen, the average sale price is 1750 yen, the most frequent purchase price range is 1600 yen, and so on, and the information processing system can be easily derived. Since the information that Mr. T, who is ranked first, purchased for 790 yen and sold for 2350 yen can be easily derived by the information processing system, such a verification chart of the brand purchase time can be easily derived by the information processing system.

(Effects of stock investment trend charts of other investors (Fig. 106))
There are many data derived for the first time in the information processing system, and this data is one of them. For the investor, the period during which the stock A was held is the period during which the funds were held. During that period, some people are buying and selling well, while others are buying at high prices and failing. When this information comes out, it is an invention that makes investors more visible and triggers a big change in investment behavior. In the information processing system, these can be automated, calculated by form input, and displayed on the chart in such an easy-to-understand manner. ..

(Specific example of stock investment trend chart of other investors (Fig. 106))
Since it is possible at all times of all stocks, for example, it is possible to display the text as shown on the left of FIG. 106 on the information processing system, and since these numbers are all derived from the database, the numbers. If you prepare the text according to (table set method), you can immediately display it on the information processing system.

(Definition and issues of automatic evaluation of ownership status)
The holding status includes the holding status of stocks (purchase data of investment products) (sell data when entering from selling). This transaction data includes the type of brand (investment product brand), purchase unit price, and purchase date. Normally, these stocks are traded in the market, and are trading data as a result of selecting the stock from various stocks that can be purchased. If you choose a different stock, the evaluation of the current holding status will change significantly. In other words, the market price after that will show different circumstances depending on the brand. If the stocks held are different, the evaluation of the holding status will change depending on how the stocks have changed. For example, assuming a case where A brand was purchased in May 2020 and continues to be held at the end of 2020, the market value of A brand at the end of 2020 was 20% higher at present. It is reflected in the holding status of. However, if the S issue has a market price increase of 50% at the end of 2020, and the Z issue has a market value of -20% at the end of 2020, the A issue was not the optimal choice. It is defined as the automatic evaluation step of the holding status to reflect this.

(Effect of automatic evaluation of possession status)
How will the above evaluation be realized? There were various options other than the selection of brand A at the time of purchase. For Japanese stocks, there are 3900 stocks to choose from. If you make a stock price table for these stocks, the horizontal axis is the stock, the vertical axis is the date, and the crossed place is the stock price of the day (either the low price to the high price of the day's stock price can be the closest price or the closing price. , Other stock prices are acceptable) Make a table. Then, if it is the A brand, it can be referred to as 500 yen in May 2020 and 600 yen at the end of 2020. A stock, ... If you take the stock price of 3900 stocks and find the rate of increase / decrease, you can rank the rate of increase / decrease. For example, if the stock with the highest rate of increase / decrease is the above-mentioned S stock, it may have been able to enjoy a 50% increase. Simply changing the brand of the purchase will make a big difference in performance in this case. It is possible to add this to the evaluation. It is possible to calculate the average value, and out of the 3900 stocks, the A stock can be expressed as 520th, and in the case of the best selection, the unrealized profit and loss will increase by this amount, and the total profit and loss will also be affected by this amount. Expressions such as giving are also possible.

It is possible to change the brand, but it is also possible to change the time with the same brand. For example, if the purchase of brand A was in May 2020, but in July 2020 it would be higher and the profit would be weaker, it would be possible to evaluate this with the previous table. On July 1, 2020, it was 550 yen, and the fact that the profit margin was reduced by 50 yen can be said to be one of the merits of being able to purchase early. Adding these evaluations is defined as an automatic evaluation of the holding status.

(Effect of automatic evaluation of ownership status)
In the case of investment products, if there is a market, there are many alternatives, and it is normal for investment results to change significantly simply by changing the brand. Also, because you have the freedom to buy at any time, time is also an option. It will be possible to evaluate the selection of stocks, the timing, and a mixture of both. For example, in the case of the above case, if the stock is S instead of A, the profit has changed so much, the average is like this, the choice at this time was correct or failed, and why it failed. Next, you will be able to understand where to improve.

(Specific example of automatic evaluation of holding status)
(Specific example 1)
The information processing system displays the degree of improvement in profit and loss in the best case (selection of S brand in the above case).

(Specific example 2)
The information processing system displays the difference in the unrealized loss amount when the average case (the average rate of increase / decrease of 3900 stocks in the above case) is applied.

(Specific example 3)
The information processing system displays the order of the selection of the A brand among the options of the 3900 brand.

(Specific example 4)
The information processing system clearly shows the difference between the technical indicators of the A brand and the S brand at the time of purchase, and asks the user to use them as the next food.

(Specific example 5)
The information processing system displays the current status of the people who purchased the S brand at the time of the purchase decision in group units (such as the group of people who still own it), and that group currently owns it. Show what the brand is.

(Specific example 6)
The information processing system displays how much profit or loss is increasing when not only the A issue but all the issues currently held are in the best case (if the issue held is the B issue, 2019 7). The best stock in the month will be another stock).

(Specific example 7)
The information processing system displays whether the case of the specific example 6 is an average case, how high the order of one's choice is, whether a good judgment is made, or a bad judgment is made.

(Specific Example 8)
The information processing system displays when the best purchase time is, and how much the profit or loss has changed if the best purchase time is delayed and the best selection is made. The information processing system displays the technical index value at that time and the technical index value at the time of actual purchase.

(Automatic evaluation of trading status)
The procedure is the same as the automatic evaluation of the holding status, and the evaluation at the time of sale as well as the purchase is added, but it is the same as the automatic evaluation of the holding status. However, points specially related to the automatic evaluation of trading status will be added at any time.

(Linkage between holding status evaluation and brand information)
The holding status evaluation process is the evaluation of the holdings, and has the role of connecting the current situation and the future, which are the results of past trading, and changing the present time will change the future. The trading results (trading data), which are the results of past trading, and the stocks currently held (holding product data) are linked, and evaluation from both sides is important.

The stocks currently held (holding product data) are linked to charts, technical indicators, business performance, etc. in the trading data to be aggregated, and are managed by the trading data. From the trading data to be aggregated to the evaluation steps up to this point, the date at the time of purchase and the purchased brand are linked. Therefore, the owned products used in this holding status evaluation are also linked to the technical index values, charts, performance, etc. at the time of purchase, and they are updated daily to create time-series data. In the process of creating the trading data to be aggregated, the trading data and the owned product data are completely linked, and it exerts a powerful power in this holding status evaluation. An evaluation index based on trading data and various indexes based on owned product data are linked to exert a special effect.

This point will be described below.

At the stage of the trading data to be aggregated, the stock code and the technical index value are linked by the relationship between the purchased product and the purchase date. Furthermore, daily updates are performed, technical index values are updated, daily updates are made, and stock price data is also updated. From the purchase price, the market price gradually changes and is brushed up every day. As a result, on the holding status evaluation screen, changes in unrealized profit and loss and information on the holding products are associated, and when the link of the holding products is clicked, the stock information and stock news are linked.

This is common information in itself, but what is important is the diagnosis result of past trading data, comparison with other investors and stocks, ranking result, etc., and information on purchased products and past trading. The results of the history and the current holdings are forming the present, and we must make important decisions as to whether the future will change.

In other words, the holding status evaluation must contribute to that. The same is true for subsequent diagnoses and advice. First of all, it is important to evaluate the current situation.

The above-mentioned automatic evaluation of the holding status takes in information on other stocks, compares them with others, and provides new information to investors. It can be said that the information provision unique to the information processing system can be performed only because the purchase data and the brand information are linked.

(Significance of warning signal generation by evaluation index)
The status of stocks held changes from moment to moment. I often overlooked it without knowing that it was down before I knew it. These are watched and a warning signal is issued, but the information processing system is linked to purchase data and past failure profits, and the meaning of this warning signal has a more special effect. It is possible to send a warning signal based on the lessons learned from past failures because it is used not only for technical indicators but also for improving problems in past trading history and points that are not working well. For example, it is an example that a warning signal is issued when the pattern is revisited by constantly repeating wrong judgments. For example, if you want to sell by rising 5%, but historical trading data shows that on average the margin is small and the investor tends to sell at a 5% rise, then after this 5% rise, those stocks It would be very convenient if we could add a function to tell how it was. The past stocks that sold at a 5% increase said, "The trend so far is that if you hold it for 3 weeks, the 5% increase has changed to a 15% increase. If it becomes possible to display something like "Let's do it?", The past history can also be used, and it will be useful information for buying and selling decisions. Of course, there are many things that are different from actual problems and past histories, so it is forbidden to make a judgment based on this alone, but as one of the information, information is provided only by the information processing system.

(Problems of conventional technology)
If the warning signal is linked to the stock price data, everyone who owns it should receive the same warning signal. However, the warning signal of the system is also linked to the past trading history, and it is possible to transmit the warning signal together with the information.

Securities companies also have the function of sending a signal and delivering an e-mail when the technical index becomes like this, but it is not generally reliable. It's very different from them.

(Action of warning signal generation by evaluation index)
The warning signal of the technical index is simple as to how to generate the warning signal. For example, the information processing system can easily output the warning signal when the RSI of the purchased product becomes 80% or more. How can we go one step further and use past trading history to signal alerts? The average number of trading days and the average rate of return are recorded daily in the evaluation indexes calculated by the information processing system, which is numerous in the fifth step. With reference to this, the average holding period of the investor up to now is calculated by the information processing system, and it is easy for the information processing system to present it first. Sell in 3 days on average, if the turnover rate is high, the average holding days up to the latest is 3 days, the average winning profit margin is 2%, but if it is a stock so far, it is 8 days instead of 3 days If you own it, it has changed from 2% to 6% on average. Being able to convey this situation will be a factor in making a decision. If you hold it on the 8th instead of the 3rd, the result has changed because the information winning system that traces the change in the market price after the sale can be easily derived. be.

(Effect of warning signal generation by evaluation index)
Of course, it is not possible to swallow all the warning signals generated from this past trading history. This is because the movement is always different from the past. However, it can provide one powerful judgment material. Moreover, since it is information given only to the investor and is provided by combining past trading data and the current holding status, it is very valuable information provision.

(Specific example of generation of warning signal by evaluation index)
First of all, the important thing is the KPI warning signal decided in the 5th step. Since there are many other evaluation indexes calculated by the information processing system, select them as appropriate.
In addition, the KPI calculated by the information processing system from Mr. A's trading data is added to the holding status evaluation and displayed. When the owned product falls below the bid price while adding the KPI item to the status evaluation of the owned product, managing the actual profit, and telling the user whether it is improving or worsening. For users whose unrealized loss rate improvement is an urgent issue, we will support performance improvement by calling attention again.

(Significance of evaluation utilizing trading data subject to aggregation by investment target)
One of the information associated with the possession status evaluation is the possessed product. The previous example shows the generated data generated by the information processing system from the association between the owned product and the purchase date, but it is the information processing system that the owned product is also associated with various information. The data of trading data to be aggregated by investment target can be mentioned in. If the stocks held are linked to the trading data to be aggregated by investment target, everything that can be done with the trading data to be aggregated by investment target becomes possible.

(Problems of the conventional method)
Conventionally, information on owned products is often linked to brand information. It is linked to the company's business performance, charts, business forecasts, company profile, stock news, etc. What is the difference between this and the trading data that is subject to aggregation by investment target?

(Effect of evaluation utilizing trading data subject to aggregation by investment target)
It is possible by linking this information to the holding stocks in this holding status evaluation, which is the "extraction condition: stock = holding stock" of the trading data to be aggregated by investment target. This makes it possible to retrieve all the information that appears in the trading data that is subject to aggregation by investment target. Not only the type of corporate performance and charts, but also the winning percentage of the stock, how other investors are behaving, whether investors who purchased at the same time still own it, the stock is compared to the average. Whether it is superior or inferior, and by using the trading data to be aggregated by period, the status of the issue in the holding period can be understood in more detail.

(Effect of evaluation utilizing trading data subject to aggregation by investment target)
Unlike mere brand information, this provides a variety of judgment factors. As a result of all the actions of other investors, their own trading history, trends of other stocks during the period, etc., it is possible to provide information unique to the information processing system with various withdrawals. It can be said that all the effects are produced because of the consistent and linked system.

(Specific examples of evaluations that utilize trading data subject to aggregation by investment target)
In addition to the above, all the cases listed in the trading data to be aggregated by investment target and the trading data to be aggregated by period can be withdrawn here.

(Definition of linked ownership status evaluation)
The fifth flow from the left in FIG. 32 is the interlocking holding status evaluation, which is performed after the fourth trading status evaluation from the left. The linked holding status evaluation is defined as the linked holding status evaluation because it is linked to the trading profit / loss evaluation, not separately.

When evaluating the holding status based on the trading data to be aggregated, the trading data below the unrealized profit / loss level is processed, extracted, created, and the evaluation index is calculated by the information processing system in the evaluation index calculation step. Evaluating the holding status of the aggregated target by integrating the evaluation index, trading profit and loss, and cash is defined as linked holding status evaluation of the aggregated trading data.

(Issues for interlocking ownership status evaluation)
As can be seen from the breakdown of the valuation amount of 2 million yen at point B in FIGS. 34 and 35, the trading status of the counter-trading (the fourth evaluation of the trading status from the left in FIG. 32) is the buying and selling of the trading status evaluation at time B. Is a trade made in the past and consists of confirmed trade data. To add a little supplement, the upper, middle and lower figures in Fig. 34 are cases where the funds of 500,000 yen have become 2 million yen, but they have different meanings. Regarding the middle figure, the trading profit / loss is 500,000 yen, the unrealized profit / loss formation fund is 1 million yen, and the unrealized profit / loss is 1 million yen. On the other hand, in the figure below, the trading profit / loss is 1 million yen, the unrealized profit / loss formation fund is 1.5 million yen, and the unrealized profit is 500,000 yen. The contents are different, and the figure below works well, but now you can see that the figure in the middle shows better results. To explain with this simple example, it is necessary to evaluate that the lower figure is high in the trading situation evaluation and the middle figure is high in the holding situation evaluation. The trading status is a past accumulation, and the current holding status is a simple diagram showing that it stands on the accumulation. In other words, in order to evaluate the holding status, the evaluation of the trading status is indispensable and linked, and this is defined as the linked holding status evaluation.

There is a change in the trading situation, and as a result, the trading profit / loss is included and the profit / loss formation fund is increased / decreased, and the principal + trading profit / loss (case in Fig. 34) -cash (case in Fig. 35) (unrealized profit / loss constituent funds) Based on the standard, the current holding status of the subject of the aggregation is established. In the holding status evaluation of the trading data to be aggregated (third from the left in FIG. 32), the trading status evaluation is arranged in parallel, and the past trading and the current holding status are processed side by side. On the other hand, in the linked holding status evaluation, it is possible to evaluate the current holding status affected by the trading status result and the cash ratio. This difference is due to the difference that the former is unrealized profit / loss level trading data and the latter is linked unrealized profit / loss level trading data. In the former case, cash and trading profit / loss are not included in the trading data, but in the latter case, cash and trading profit / loss are incorporated, and the leverage effect and compound interest effect index are also incorporated in the model (including linked type). See the P & L level trading data section). The reason why the current holding status can be grasped more accurately by one or two steps is the cooperation in which the management items are increased by the linked unrealized profit / loss level trading data at the stage of creating the trading data. The usual portfolio analysis and the list of stocks held by securities companies are all the former, and with the latter technology, in addition to that, the contribution of past trading profit and loss and the compound interest effect are reflected. This is a very important technique for assessing ownership. It will be explained next.

(Effect of interlocking possession status evaluation)
Indispensable for explaining the linked holding status evaluation is the concept of linked unrealized profit / loss level trading data. The model explained in this section is easy to understand, so I will reprint it. Let's start with the simplest example. Assuming that Mr. S's principal (1 million yen) was dropped 100% and continued to rise and tripled, looking at the case where the profit was confirmed here, 1 million yen + 2 million yen = 3 million yen The valuation amount is yen, and the gross profit amount is 2 million yen and the principal amount is 1 million yen. On the other hand, the unrealized profit / loss formation fund is 0 because it was sold, the cash is 3 million yen, and the unrealized profit / loss is not held.

Next, Mr. S spends 100% of this 3 million yen to purchase brand A, and if brand A rises by 10%, the total valuation is 3 million yen + 300,000 yen = 3.3 million yen. The profit amount is 2.3 million yen and the principal is 1 million yen. On the other hand, since 100% of the unrealized profit / loss formation fund is invested, the unrealized profit / loss will be 3 million yen and the unrealized profit / loss will be 300,000 yen (see Mr. S in Fig. 108).

On the other hand, even if you start with the same 1 million yen, Mr. A who has not made a profit yet, even if you purchase the same A brand in full at the same time, the total evaluation amount is 1 million yen + 100,000 yen = 1.1 million yen, and the total profit amount Is 100,000 yen and the principal is 1 million yen. On the other hand, since the unrealized profit / loss formation fund is 100% invested, it will be 1 million yen and the unrealized profit / loss will be 100,000 yen. Even if you start with 1 million yen principal at the same time and invest the full amount of A brand at the same time, Mr. S has an unrealized profit and loss of 300,000 yen with an unrealized profit and loss formation fund of 3 million yen, while Mr. A Is an unrealized profit / loss formation fund of 1 million yen and is only 100,000 yen unrealized profit / loss. Mr. S has a compound interest effect, so even with the same 10% increase, it will increase by 300,000 yen, which is a 30% increase when considering the principal. On the other hand, Mr. A still has an increase of only 10% from the principal (see Mr. S and Mr. A in Fig. 109). This is because the compound interest effect is not working. Here, the concept of unrealized profit and loss formation funds comes into play. The snowball increase is due to the increase in this unrealized profit and loss formation fund. Speaking of the comparison between Mr. A and Mr. S, there was a difference of 1 million yen and 3 million yen before I knew it, so the latter is becoming more and more superior.

Furthermore, in the case of margin trading, (principal + trading profit / loss-cash) x leverage ratio will be added to the model. By adding the leverage rate to one of the items, the compound interest effect index will further increase. For example, if the leverage rate is 1x, the compound interest effect index is 3 in the previous example of Mr. S, but assuming that Mr. Z doubles the leverage, the unrealized profit and loss formation fund is doubled to 6 million. It becomes a circle. 10% of 6 million yen is 600,000 yen (see Mr. Z in Fig. 109). Even with the same rise in the A brand, Mr. A will be 100,000 yen, Mr. S will be 300,000 yen, and Mr. Z will be 600,000 yen (see FIGS. 109 and 88). The reason why this difference becomes clear even with a 10% increase in the same A brand is that Mr. S has a compound interest effect, and Mr. Z has a double effect of leverage and compound interest, and evaluates the current holding situation. Need to come in with these models. This is the result of doubling the leverage rate and doubling the compound interest effect index. By adding this leverage effect to the items, the effect of clarifying the principle of leverage and the actual condition of the compound interest effect is immeasurable (for example, the difference in notation as shown in FIG. 88 is an example).

The information generation unit 3021 extracts (or classifies, aggregates, processes) trading data below the linked unrealized profit / loss level based on the aggregated trading data and component trading data created in the step of creating the aggregated trading data. It is created, the evaluation index is calculated in the evaluation index calculation step, and the holding status of the aggregation target is evaluated by integrating the evaluation index with the trading profit / loss and cash.

(Effect of linked ownership status evaluation)
The unrealized profit / loss formation fund is the "amount obtained by subtracting cash from the principal" if the starting point is cash, and if a certain period of time has passed since the starting point was started from the principal. “Principal + trading profit / loss-cash” (see the middle section of FIG. 35).

The unrealized profit / loss formation fund is based on the amount obtained by subtracting the remaining cash from the principal and the trading profit / loss from the start time, which indicates the purchase amount of the investment product currently held at the start time. A comparison between the purchase price at the start and the current price is more suitable for evaluating the holding status.

Explaining with FIG. 36, the unrealized profit / loss formation fund (upper part of FIG. 36, 500,000 yen + 16.25 million yen-10.69 million yen) obtained by subtracting cash (10.69 million yen) from the trading profit / loss (16.25 million yen) from the start time. Starting from (= 6.05 million yen), this unrealized profit and loss formation fund can be grasped from various aspects.

Unrealized profit / loss formation fund = Purchase amount of currently owned products after point A + Purchase amount of currently owned products before point A (6.05 million yen in the middle of Fig. 36 = 3.93 million yen + 2.12 million yen)
Unrealized gain / loss formation fund + Unrealized gain / loss + Cash = Current valuation amount (2.77 million yen (2.12 million yen + 650,000 yen) + 9.33 million yen (3.93 million yen + 2.78 million yen + 2.62 million yen) + 10.69 million yen = 22.79 million yen )
(Principal + Trading profit / loss from the start-Cash) + Unrealized profit / loss + Cash = Current valuation amount ((500,000 yen + 16.25 million yen-10.69 million yen) + 6.05 million yen (650,000 yen + 2.78 million yen + 2.62 million yen) + 1069 10,000 yen = 22.8 million yen)
In the above formula, the right term is the current situation, and the left term is the sum of the profits accumulated from the start. The unrealized profit / loss formation fund is the holding status generated as a result of the trading status, and the unrealized profit / loss formation fund based on the result of the past trading status and the evaluation of the current holding status are evaluated in chronological order. It will be possible.

The unrealized gains / losses that evaluate the holding status are linked to change depending on the trading profit / loss status. Moreover, since the effect of leaving it in cash will also come out, the linked holding status evaluation will enable a more advanced evaluation.

In addition to this, the leverage effect and compound interest effect index have been added as management items in the linked unrealized profit / loss level trading data (see the section of linked unrealized profit / loss level trading data), and the actual state of holding status is clarified. There is an effect.

(Specific example of linked ownership status evaluation)
FIG. 37 is a diagram showing an evaluation example of the interlocking possession status according to the present embodiment. In the upper part of the information generation unit 3021, the principal is 1 million yen, and the current evaluation amount (evaluation amount at time B) has increased to 2 million yen. As a result of the evaluation of the trading profit and loss of 500,000 yen, which was confirmed in the above, and the unrealized profit and loss formation fund of 1.5 million yen, which is the increased fund, is increased to 2 million yen. Evaluate separately from the evaluation of the yen. It is clear that the formation of unrealized gains and losses comes from the results of trading gains and losses, and the effect of including the compound interest effect in the evaluation model is great.

On the other hand, in the lower row, when evaluating trading data in which the principal is 1 million yen and the current valuation amount (valuation amount at time B) has increased to 2 million yen, 1 million yen is settled at 1.5 million yen. The result was the evaluation of the trading profit and loss of 500,000 yen, leaving the cash of 500,000 yen, increasing the unrealized profit and loss formation fund of 1 million yen to 1.5 million yen, and combining the unrealized profit of 500,000 yen and the remaining cash of 500,000 yen. There is.

In each case, the unrealized profit is 500,000 yen, the trading profit is 500,000 yen, the valuation is 2 million yen, and the principal is 1 million yen. This is a concrete example of how the unrealized gain formation of 500,000 yen with the funds of 1 million yen and the unrealized profit formation of 500,000 yen with the funds of 1 million yen in the latter change.

The same applies to linked comparisons, linked rankings, linked diagnoses, and linked advice for aggregated trading data.

(Definition of interlocking evaluation)
(Definition of interlocking evaluation)
When evaluating the trading status and holding status based on the trading data to be aggregated, in 11, the trading data below the trading profit / loss level is extracted (or classified, aggregated, processed) and created, and the evaluation index is calculated in the evaluation index calculation step. Then, evaluate the trading status of the aggregation target, extract (or classify, aggregate, process) the trading data below the linked unrealized profit / loss level, create it, and calculate the evaluation index by the information processing system in the evaluation index calculation step. , Evaluating the holding status of the aggregation target based on the evaluation index, trading profit / loss, cash, leverage effect, compound interest effect index, etc. is defined as linked evaluation of the aggregation target trading data. It is also essential to understand the linked unrealized profit / loss level trading data and linked holding status evaluation, so refer to that section as well.

(Unrealized profit / loss formation fund)
FIG. 36 is a diagram showing an example of linked evaluation of aggregated trading data according to the present embodiment. The unrealized profit / loss formation fund is the stock price valuation at the time of purchase (the purchase price of the stock currently held). As shown in FIG. 36
6.05 million yen (Unrealized profit / loss formation fund)
= 3.93 million yen (unrealized profit / loss formation fund A) +2.12 million yen (unrealized profit / loss formation fund B)
3.27 million yen (unrealized profit increased from point A)
= 2.62 million yen (= 933-671) + 650,000 yen (= 277-212)
(Issues of interlocking evaluation)
The trading status of the counter-trading consists of trading data that has been conducted and confirmed in the past. As a result, the trading profit / loss increases / decreases from the starting valuation amount, and the current holding status is established based on "starting valuation amount + trading profit / loss-cash". In the old method of evaluating the aggregated trading data, the past trading status and the current holding status are processed side by side.

(Action of interlocking evaluation)
The information generation unit 3021 creates and evaluates trading data below the trading profit / loss level extracted (or classified, aggregated, processed) based on the aggregated trading data and component trading data created in the aggregation target trading data creation step. In the index calculation step, the evaluation index is calculated by the information processing system, the trading status of the aggregation target is evaluated, and the evaluation index is calculated by referring to the trading data below the linked unrealized profit / loss level based on the aggregation target trading data. The evaluation index is calculated by the information processing system in the step, and the holding status to be aggregated is evaluated by integrating the evaluation index, cash, trading status evaluation, leverage effect, compound interest effect index, and the like.

(Effect of interlocking evaluation)
It is possible to evaluate the past trading status and the current holding status based on the resulting funds in chronological order. In order to evaluate the holding status, not only the evaluation of unrealized gains and losses, but also the status of trading profits and losses that created the unrealized gains and losses, the cash status, the leverage rate, the compound interest effect index, etc. Is creating the situation. Since these are not different things but are interlocked, interlocking evaluation enables more advanced evaluation.

(Unrealized gains / losses are linked to change depending on the trading profit / loss situation and cash situation)
The current valuation can be seen from various aspects. FIG. 36 is a diagram illustrating this. The appraisal value of 22.8 million yen can be viewed from the perspective of principal and profit (1) or from the current holding status (2).

Case of current holding status evaluation at the start of principal (1) 22.8 million yen (current evaluation amount) = 500,000 yen (principal) + 16.25 million yen (trading profit / loss) + 6.05 million yen (unrealized profit / loss)
(2) 22.8 million yen (current valuation amount) = 6.05 million yen (unrealized gain / loss formation fund) + 6.04 million yen (unrealized gain / loss) + 10.69 million yen (cash)
(3) 22.8 million yen (current valuation amount) = 45.6 times the principal (500,000 yen) Therefore, in the current holding status evaluation, not only the unrealized gain or loss but also the evaluation of how many times the principal was multiplied. It is necessary to add to the evaluation the amount left in cash, the evaluation of trading profit and loss, and the relationship between trading profit and loss and unrealized profit and loss. In other words, in order to evaluate the current accurate investment situation, principal, trading profit / loss, cash, and unrealized profit / loss affect, so it is necessary to incorporate these models as well.

(Specific example of interlocking evaluation)
When evaluating trading data with a principal of 1 million yen and a current valuation of up to 2 million yen, a trading profit / loss of 500,000 yen, which is a profit of 1 million yen at 1.5 million yen, and a trading profit / loss As a result, it is clarified that the formation of unrealized gains and losses comes from the results of trading gains and losses, while separating from the ongoing evaluation of unrealized gains and losses of 500,000 yen, which has resulted in increasing the increased funds of 1.5 million yen to 2 million yen. Therefore, the effect of including the compound interest effect in the evaluation model is great.

On the contrary, when the price changed from 1 million yen to 900,000 yen, the trading profit / loss decreased from 1 million yen to 800,000 yen by 200,000 yen, but the holding profit / loss based on 800,000 yen increased by 100,000 yen. If so, it can be evaluated that the holding situation is improving.

(Specific example of interlocking evaluation)
The evaluation process in Fig. 36 is based on the trading profit and loss of 16.29 million yen, which generated the purchase amount of 6.05 million yen, cash of 11.69 million yen, and the principal of 500,000 yen. There is an evaluation of the holding status.

This is an evaluation model that explains the compound interest effect. This matter is detailed in the linked unrealized P & L level trading data. By calculating the evaluation index based on this linked unrealized profit / loss level trading data and grasping the current longevity situation, the effect of being able to appropriately perform the current evaluation is exhibited.

(Evaluation display step)
After the evaluation step of the evaluation process is called the evaluation display step.

Since what is evaluated and how is evaluated by the sixth step, the step of displaying the evaluation in an easy-to-understand and easy-to-understand manner is this display step.

(Prior technique for displaying evaluation steps)
If it is just a list of evaluation index numbers, it is not easy for anyone to understand, and it may require reading, familiarization, and the power of others, but at this step, what to evaluate, how to evaluate it, what kind of evaluation result is In order to display in an easy-to-understand manner, it is necessary to select a display method according to the evaluation index and what to evaluate.

(Definition of evaluation display step)
In the evaluation display step, it is necessary to select an appropriate display according to the target, the type and number of evaluation indexes, and the evaluation method.

For example, even in graphs, the expression method changes depending on the vertical and horizontal axes to be determined, and there are pie charts, bar graphs, line graphs, and charts. Even in the table, the table that can be taken differs depending on the vertical axis and the horizontal axis, and the numerical values handled such as the composition ratio, the numerical value, the average value, and the total value also differ. In addition to the visual representation of graphs and tables, text display may be used. In this case, it is important to display a combination of text and numbers. Properly linking the meaning of numbers with the text allows for persuasive expressions. Of course, these may be displayed to investors, or may be made into news and expressed to an unspecified number of people. Up to the evaluation process of the sixth step, it is necessary to change whether the text is good, the graph is good, the bar graph, etc. according to the evaluation result obtained, and that step is referred to as this display step.

(Problems of conventional technology)
No matter how much or bad the rating is, if the display is not properly displayed, it will be difficult to understand, and it will not be possible to improve or move in the right direction using the rating. Although it is the final step of the evaluation process, if this display can be made appropriate, the evaluation of the evaluation target can be properly understood, and the next step for improvement can be taken.

(Action of evaluation display step)
Up to the fifth step of the evaluation process, the evaluation target is determined, the purpose and method of evaluation are determined, and the trading status and holding status are evaluated using various evaluation indexes calculated by the information processing system. At this time, the type of trading data to be aggregated, the type of component trading data, the type of profit and loss, the numerical value of the evaluation index, etc. are determined, and the target is evaluated using these. There are various types, and the step of deciding what display method, which number to use and how to display based on the obtained information is the evaluation display step.

(Effect of evaluation display step)
By displaying the evaluation in an easy-to-understand manner for the user who sees the display, the steps up to the sixth step are utilized, and a different effect is exhibited.

(Specific example of evaluation display step)
For example, in order to evaluate the trading profit / loss of issue A in 2020, create the trading data to be aggregated for issue A (collect the trading data to be aggregated for Mr. A, Mr. B, Mr. C, etc.) and only the trading data of issue A. Is extracted), and the year component trading data of issue A is created with the year as a component. As a result, trading data for the A issue in FY2018, FY2019, and FY2020 is created (steps 2 to 3). In order to evaluate trading profit / loss, trading data below the trading profit / loss level is created for each of the A issue in FY2018, FY2019, and FY2020. Among them, the trading profit / loss level of 2020 is created (it is possible to have it in the previous process), and the trading profit / loss amount (total value) of the A issue in 2020 is determined. For example, if it is 50 million yen, this 50 million yen will be the amount of money earned from various trading of A brand in 2020.

The evaluation target of the trading profit of 50 million yen of the A brand in 2020 is decided (steps 2 to 4), and how to evaluate it is the next stage, and this 50 million yen was earned. That's the reason. The information processing system calculates various evaluation indexes that are the decomposition elements, the components, and the related elements that are the reasons for generating the trading profit, such as the number of trading, the winning rate, the winning profit, and the losing loss, which are the components. (Fifth step). It is a process of evaluating the trading status of the A brand in 2020 (the step) using these evaluation indexes calculated by the information processing system.

These steps are the steps that bridge which evaluation index is used and what kind of expression is used. For example, in order to accurately express the trading profit and loss of issue A in 2019, it is important to decide which evaluation index to use and what kind of expression to use. It is performed in the 4th to 6th steps, but how to express it in a user-friendly manner is performed in the display step of this evaluation process.

It may be expressed in sentences, in a list of numbers, in a graph such as a pie chart, a bar graph, or a chart, or in a table.

(Chart Specific Example 1)
Charts are suitable for trading profits of stocks.

It is said that the price movement of the A brand in 2020 was expressed on the stock price chart, the buying price buying time was plotted, the selling price selling time was plotted (expressed by dots and stars, etc.), and the average was bought here and sold here. The display can be expressed visually.

(Chart Specific Example 2)
The price movement of the A stock in the previous fiscal year 2020 is represented by a stock price chart, the stock price purchased at the lowest price is plotted, the stock price sold at the highest price is plotted, the average value is plotted, and only one's own buying and selling is displayed. The average and maximum price range trading data is displayed in red, the range of buying and selling advice is shown for each adviser, the color is changed for each securities company, and the average trading range is shown. Expression is possible.

For example, if you display the unrealized gains / losses of issue A at the end of 2020 on a chart, the current price at the end of the year is 670 yen, the bid price of Mr. A is 500 yen, the bid price of Mr. B is 550 yen, and the average bid price is 600 yen, which is the highest. It is very easy to see and understand the chart, such as the bid price of 670 yen, the lowest bid price of 480 yen, and the average holding period of 3 months. In this case, the trading data to be aggregated is the A issue in 2020, the component trading data is for each investor, the profit / loss is the unrealized profit / loss, and the evaluation index is the unrealized profit / loss and the bid price, the holding period, the average holding period, and the like. To evaluate this, the chart above is a self-explanatory and easy-to-understand display method.

(Specific example 2)
Further, for example, if the investor is used as a component based on the above-mentioned 2020 A issue trading data, the 2020 A issue can be divided into A's trading data and B's trading data. By using profit and loss as trading profit and loss and using the number of trades as an evaluation index, it is effective to make it clear at a glance who earned the most and how.

A pie chart is suitable for clearly displaying who earned the trading profit of stock A in 2020, and the person who earned the most is each evaluation index (number of trading, number of days held, winning profit margin and losing loss rate). Etc.) is made into a pie chart to display the number for each investor and the average number, and the process of the sixth stage is to select an appropriate expression method such as which number of the investor is superior to the average.

The information processing system determines the target trading data by combining the aggregated trading data and the component trading data. Determine the target profit and loss in the third stage. In the fourth stage, the evaluation index that affects the profit and loss is calculated by the information processing system. Various evaluations are performed using the evaluation index calculated by the information processing system. The sixth stage is how to express the evaluation.

(Specific example 3)
If it is a combination evaluation process in which Mr. A's trading data to be aggregated uses the period for each year as the component trading data, the total profit / loss as the profit / loss level, and the evaluation index as the evaluation amount, the horizontal axis should be in a line graph format. For example, by setting the year and the vertical axis to the valuation amount, the transition of the valuation amount every other year becomes clear and easy to understand.

(Specific example 4)
The pie chart is easy to understand when calculating the composition ratio, but it is this pie chart that makes it easy to understand who raised the trading profit of stock A, and which stock raised the trading profit of Mr. A? Let's make a pie chart that is easy to understand.

(Specific example 5)
The stacked bar graph is, for example, an easy-to-understand display method for the following cases.

Create component trading data for each fiscal year from Mr. A's aggregated trading data, and create component trading data for each issue when evaluating the trading situation with profit and loss as winning profit and evaluation index as winning profit. By doing so, the winning profit of each stock for each year is required.

Along with the transition of winning profits in 2020, 2019, and 2018, for example, the composition of winning profits in 2020 is 30% for A stock, 40% for B stock, 20% for C stock, and others. 10%. In 2019, 70% of D stocks and 30% of other stocks can be seen at a glance from the stacked bar graph. This kind of expression is possible by taking the composition ratio of each issue, with the year on the horizontal axis and the winning profit on the vertical axis.

(Specific example 6)
Use it properly according to each evaluation target and evaluation index, such as a% display graph used to express changes in the composition of the composition ratio in an easy-to-understand manner, and a hexagonal graph that makes it easy to express which evaluation index is strong or weak. This is the sixth step.

(Specific example 7)
Also, in the case of investment target trading data, it is important to use charts in order to express them in an easy-to-understand manner. The horizontal axis is the year and month, the vertical axis is the stock price (4 prices, closing price, etc.), and based on the stock price chart, plot your own buy price purchase date and plot the sell price sale date. , It is an example to display how much trading profit and price range have been obtained. It is possible to display at a glance whether or not the product was successfully sold or bought.

(Specific Example 8)
For example, the investment target trading data of stocks is used as the aggregated trading data, the investment type is used as the component trading data, the profit / loss is used as the total profit / loss, and the total profit / loss ratio and the total profit / loss composition ratio are used as evaluation indexes. When evaluating the total profit / loss of these stocks, the total profit / loss of these aggregated stocks is 300 million yen, the day trading type is 10 million yen, the swing trading type is 50 million yen, and the medium- to long-term type is 200 million yen. When it costs money, the horizontal bar graph is one of the easy-to-understand expressions.

(Specific example 9)
If you want to evaluate Mr. A's aggregated trading data at each profit / loss level, and evaluate Mr. A using total profit / loss, trading profit / loss, unrealized profit / loss, winning profit / loss loss, etc. as evaluation indexes, Type graphs and waterfall types are suitable as an easy-to-understand expression method.

(Text specific example 10)
For example, when stocks with upward revisions (stocks whose corporate performance greatly exceeds expectations) are captured by EDINET, etc., and when and which stocks have a 50% significant update of sales from 10 billion yen to 15 billion yen. In addition, for users who own them, such a text (A brand you own has a significant upward revision of the forecast from 10 billion yen to 15 billion yen in sales at 15:00 on January 10th. A mechanism to automatically deliver news such as announced.) Is conceivable. This is an application version of automatic evaluation of ownership status. Of course, it is the same not only for the owned users but also for distributing it as news to everyone.

(Text example 11: A specific example of possession status evaluation)
For example, it is possible to incorporate the update frequency of Twitter issues into trading data and inform the users who own the issues (increased frequency of issue updates) whose attention has risen sharply to individual investors.

(Text example 12: A specific example of possession status evaluation)
When the holding stock has a feeling of overheating from the technical index and a decline is expected with a high probability, the holder is told, "The stock has a very high RSI of the technical index and the deviation rate from the 25-day moving average. It is also possible to display the text data "Be careful because it exceeds%." On the user terminal. This is also a form of possession status evaluation. Of course, this includes not only the case of delivering to a specific user but also the case of delivering to everyone as news.

(Text example 13: A specific example of possession status evaluation)
When the rights information to carry out a stock split was updated (updated the rights data in the trading data) for the stocks held, the stock split of "when" and "stock name" was announced. The content is the announcement of "scheduled split date" and "two splits". After the "scheduled split date", the rights will be extinguished and the number of shares will change from "number of shares held" to "number of shares to be split". ] Can be displayed on the terminal.

(Text example 14: A specific example of possession status evaluation)
By displaying a table that compares the technical indicators of the entire cryptocurrency and the technical indicators of the entire stock for the users who own the cryptocurrency and the stock, special convenience is created for the holders. This is also possible because the holding status and the information on the investment target are linked. This is an example in which various information can be displayed on the terminal by linking the trading data and the brand information.

(Text example 15: A specific example of trading status evaluation)
The holding status evaluation is a display performed on the stocks held, while the trading status evaluation is an evaluation and display performed on the stocks being bought and sold. For example, "The stocks to be sold may now be a buying opportunity again. The moving average divergence rate is -20%, and other indicators are also firing buy signals. Why not consider it a little? It is possible to display text such as ".". This is a specific example of trading status evaluation. This is also possible because the trading status (trading data of what was sold and when) and the information of the brand are linked.

(Text specific example 16)
As a specific example of trading status evaluation, if there is a user whose task is to increase the winning profit rate with the evaluation index and the winning profit rate changes from 5% to 10%, the trading profit amount will be 1 million yen per year. In the case of AI, it is possible to add a function to notify the stock that the user who has already sold and earns a profit margin is currently buying.

(Old method of comparison process)
Investors may be compared and ranked with reference to the evaluation index calculated in the first embodiment, and information indicating the investor comparison and ranking may be generated as the evaluation index. The comparison here refers to comparing the evaluation index of the investor with the evaluation index of another investor, the average value of the evaluation index, and the like.

The new method has three comparison processes (aggregation target comparison process, component comparison process, and profit / loss level comparison process) (see FIG. 63). FIG. 63 is a diagram showing three comparison processes according to the present embodiment.

(Definition of comparison process)
The comparison process is performed through the following process, but the second step and the sixth step may be omitted.

The first step is the acquisition step of trading data. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component. The fourth step is the step of creating profit / loss level trading data. The fifth step is the calculation and selection step of the evaluation index by the information processing system. The sixth step is an evaluation process (divided into an evaluation step and a display step). The seventh step is a comparison process (divided into comparison of aggregated trading data and comparison of component trading data). The comparison process is defined as comparing the calculated evaluation index (either single or multiple) with the average or another aggregation target or component.

In the comparison process, there are conditions such as first having a comparison target, having an evaluation index to be compared, having a profit / loss of which profit / loss to improve, and by what criteria the comparison is made. It is important to determine these. When comparing the trading data of Mr. A and Mr. B, of the first to fifth steps, the second step is to classify the trading data of Mr. A and the trading data of Mr. B, and the fourth step is each. Trading profit / loss level By creating trading data (even if you have it in the previous process) and calculating the evaluation index that is an influential factor of trading profit / loss by the information processing system, the comparison target is determined and the evaluation index to be compared. Is decided, it is decided to improve the trading profit and loss, and all the above-mentioned conditions of comparing by the criteria of Mr. A and Mr. B are decided. The determination of these conditions is recorded in the storage unit 33 each time. By recording various comparison targets and various comparison methods, it will be possible to use it for AI and machine learning will become possible. The comparison process is divided into two types, one is the comparison of trading data to be aggregated and the other is the comparison of trading data of components, depending on what is compared with what. The comparison between Mr. A and Mr. B is the former, the comparison between the A brand and the B brand is also the former, and the quarterly report reference trading and the Twitter reference trading are the former. It is possible to compare purchase data with an RSI of 20% or less and purchases with a moving average deviation rate of -20% or less using technical indicators. If it is an investor as a whole, it is possible to compare by the constituent elements if it is only the target of aggregation and the buying and selling of Mr. A. The deeper the evaluation index, the larger the number of evaluation indexes, and detailed comparison is possible (comparison of profit and loss level evaluation indexes). As mentioned above, there is a comparison target (what to compare), there is an evaluation index to compare (at what level), which profit / loss is to be compared to improve (which profit / loss is to be compared as an improvement target). The comparison process requires conditions such as () and the criteria for comparison (extraction conditions for aggregated trading data, etc.), and the comparison data (comparison targets, extraction conditions, etc.) generated by these comparison processes are stored. It is saved in the part 33.

(Issues in the comparison process)
It is currently difficult for investors to compare how they are compared to others, and what is inferior to the average performers and the best performers.

(Action of comparison process)
By following the process as shown in the definition of the comparison process, the comparison will be facilitated. When comparing the trading profit / loss in 2019 and the trading profit / loss in 2020 of Mr. A, the component trading data is used, so the component comparison is suitable. When comparing the total profit and loss of the stocks of Mr. A and Mr. B, the trading data to be aggregated is compared. Decide whether to use the aggregated comparison process or the component comparison process, depending on what you are comparing. When comparing with the average, it is possible to compare the aggregated value of Mr. A and the whole with the component trading data, and the person with the highest grade calculates the maximum value of the evaluation index by the information processing system. , Shown and compared.

(Effect of comparison process)
This comparison process makes it possible to compare different objects using different metrics, providing a guide for users on how to improve.

(Specific example of comparison process)
Based on the comparison of trading profits of Mr. A and Mr. B, the comparison of winning profits of Mr. A in FY2019 and FY2020, the comparison of the trading frequency of A securities company and B securities company, and the advice of adviser a and adviser b. It can be considered from various viewpoints such as comparison of trading profit / loss ratio, trading based on the quarterly report and trading based on Twitter from various aspects, comparison of trading frequency, trading profit / loss ratio, winning rate, etc. of stocks A and B. ..

As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated, and an evaluation index according to the purpose is calculated. Therefore, even in this step, it is possible to easily compare various conditions and various forms of evaluation indexes. Although this step is only one step in FIG. 102, since the evaluation indexes have been determined by a series of cooperation, it is possible to compare the evaluation indexes of many forms and the comparisons of many objects mentioned in the present specification. It is possible.

(New method of AI machine learning comparison process)
The AI machine learning comparison process is performed through the following process.

The second step is the process of creating trading data to be aggregated. The third step is the process of creating component trading data (optional). The fourth step is the process of creating the profit / loss level evaluation index (the target evaluation index is calculated by the information processing system by the three methods).

Up to this fourth step, the target profit and loss and the target trading data are determined.

In the fifth step, the evaluation index which is a component of the target profit / loss (total profit / loss, trading profit / loss, etc.) determined in the fourth step is calculated. The fourth step can be included in the third step or can be set to another step (optional). Up to this fifth step, the target profit and loss, the target trading data (data structure), and the evaluation index that is a variable are determined.

In the sixth step, the evaluation index calculated by the information processing system is used as a comparison target, and what is good and what is easy to understand is what the target comparison target is, and which evaluation index is used in the comparison target. Machine learning is performed to determine whether to compare, and the comparison target is determined by a comparison method that seeks the optimum solution.

In the seventh step, how to compare these optimal solutions, the comparison target, is displayed in an appropriate display method. Examples of the display method include element, ranking display, comparison display, text comparison display, and the like.

(Issues in the AI comparison process)
In the comparison process described above, there are many options for deciding which comparison target to use, which profit / loss to use, and which evaluation index to use. Therefore, while it should be easy for anyone to handle, there is a problem that there are many options to decide.

Going one step further from the above comparison process, in order to maximize the target profit and loss, we will compare by adding the process of storing the evaluation index as a variable, the process of finding the optimum solution, and the process of displaying it. The process evolves into a comparison process by AI learning using machine learning.

If you decide the target profit and loss using the trading data, you will learn which comparison target and which evaluation index should be compared to be optimal, and learn the inferior points compared to the trading data of the comparison target. To go. By displaying the learned results, AI will find the optimal solution in the AI comparison process.

(Action of AI comparison process)
In addition to the above comparison process, once the target trading data and the target profit / loss are determined, in order to improve and optimize the target profit / loss, which evaluation target and which evaluation index should be used. By learning how to compare and displaying the evaluation index to be changed and how to change the evaluation index, we will approach the optimum solution. Such transactions will become possible.

(Significance of AI comparison process)
In addition to the above comparison process, we will add a process to learn how profit and loss will change if the evaluation index is changed. A method, software, or device that constitutes a storage unit 33 that stores it, an evaluation index that is a variable, a target profit / loss, target trading data (aggregated trading data or component trading data), a learning unit 34, and the like. , Database structure, learning method.

(Effect of AI comparison process)
By adding the AI process in addition to the above-mentioned comparison process, it is effective to perform machine learning on how to compare the target trading data with the optimum solution.

(Specific example of AI comparison process)
(Specific example A)
For example, if you want to improve Mr. A's total profit and loss, create Mr. A's total profit and loss data, create total profit and loss level trading data (even if you have it in the previous process), and it is a component of total profit and loss. With the evaluation index as a variable, in order to optimize with the goal of improving Mr. A's total profit and loss, we will learn which comparison target should be compared with which evaluation index, and whether it is optimal. "GA is the best comparison target, aiming for GA's winning percentage, changing the winning percentage from the current 50% to 60%, and changing the winning profit margin from the current 4% to 5%. It is an example that some patterns are displayed, such as "If you go, the profit of buying and selling 1 million yen will increase with a probability of 80% in one year", and you aim for a combination with a high probability and a large degree of change. For Mr. ZZ, another index is good, the losing loss rate is about the same, but the winning profit margin is as high as 20%, so how do you buy and sell, and if you win, you can extend the holding period. By learning the differences between brands, you can find a way to improve.

(Specific Example B)
For example, when it is desired to improve the trading profit / loss of the A stock, the trading profit / loss data of the A stock is collected by creating the trading data to be aggregated of the A stock and targeting the trading profit / loss level trading data. Trading profit / loss level of stock A Various evaluation indexes that affect trading data are calculated by the information processing system, and the influence of these various combinations on trading profit / loss is learned, and the holding period of stock A and the holding period Learn the trading profit margin, the trading profit ratio and average holding period of the person who has the highest trading profit, and learn the trends such as the purchase time and sale time of the person who has the lowest trading loss. We are buying and selling A brand close to Mr. RA who is making the largest trading profit, but compared to Mr. XA who is getting better results, in terms of buying method, holding period, selling method, frequency, etc. You can expect the effect of becoming able to understand how there is a difference and how to improve it.

(Specific Example C)
For Mr. A who buys and sells using Twitter, create component trading data for each reference medium of the trading data to be aggregated for all investors (it is possible to have it in the previous process), and buy and sell at the total profit and loss level. Create data, learn and memorize which reference medium is what kind of result. In buying and selling using Twitter, the winning profit margin tends to be low, the losing loss ratio tends to be large, and learning that it is difficult to achieve results, the method using the quarterly report, the performance-based method, the chart-based method, etc. Compared with FA by telling Mr. A, who is learning the profit and loss and evaluation index of, and buying and selling using Twitter, that Mr. FA, who is the main performer, is excellent as a comparison target. So, where and how to improve it will be possible to guide the direction of such changes.

(Specific Example D)
Create trading data by investment target based on stocks in the category of stocks, stable growth stocks, and high-growth stocks, and create total profit / loss level trading data for various investment targets of various stocks. Learn the difference between each evaluation index. Based on the learning results, if the A stock is a stock in the category of the maker stock, the HAS stock of the high-growth stock is the best for comparison, and the winning percentage and the winning profit margin of those who sell and lend the HAS stock are A. There is a display method that shows that it is so expensive compared to the stock and gives suggestions for the selection of the stock.

(Specific example E)
Create aggregated trading data by investor of group A with high performance with Mr. A, create a total profit and loss table, learn various evaluation indexes of Mr. A, learn various evaluation indexes of group A, When evaluating the holding status, if it is Group A, it is possible to display such as changing the holding status in this way.

(Learning generation method for AI comparison)
(Purpose)
We will learn which comparison target and which evaluation index can be used to improve the target profit and loss.

(Step of learning generation method of AI comparison process)
The procedure for creating aggregated trading data and component trading data, the step for deciding which profit / loss to improve, the step for calculating the evaluation index that constitutes the profit / loss by the information processing system, and the original trading. A calculation step for calculating profit and loss that changes depending on the combination of data and an evaluation index calculated by the information processing system, and a step for learning what combination is the optimum solution. include. Even if you compare Mr. A and Mr. B, there is not much difference in the index and the frequency is different, so it is judged that it is not excellent as a comparison target, and Mr. A and Mr. Z also have a trading frequency. Although they are about the same, they have a high win rate and a high rate of return, and although they are similar as comparison targets, they have a large difference in total profit and loss and are optimal as comparison targets. In particular, various findings can be obtained by comparing the winning percentage and the winning profit margin and digging deeper. It is the optimal solution for comparison.

The theme is which comparison target should be referred to in order to raise the overall profit / loss ratio of Mr. A. Mr. B's total profit / loss ratio and the values of various evaluation indexes that compose it, Mr. C's total profit / loss ratio and the values of various evaluation indexes that compose it, Mr. ZTT's total profit / loss ratio, and various evaluations that compose it. We will learn whether or not each is optimal with the comparison target, such as the value of the index. Among them, Mr. ZA is the most suitable as a comparison target, and by referring to their trading methods, brands, trading periods, etc., it can be expected that the improvement path will be clarified.

Even if there are not many discoveries in the comparison between Mr. A and Mr. B, there are many things in common in the comparison between Mr. A and Mr. ZA, and it is the learning generation step of this AI comparison process that AI judges that there are various suggestions. It will be possible.

(Definition of aggregation target comparison process)
The information generation unit 3021 generates information on the comparison of the trading status or the holding status between the standards by comparing the trading profit / loss level evaluation index or the unrealized profit / loss level evaluation index between the standards (for example, between the investment targets).

FIG. 48 is a diagram showing an example of an aggregation target comparison process according to the present embodiment. It depends on which object and what is compared. Comparing the evaluation indexes to be aggregated is the aggregation target comparison process, comparing the components is the component comparison process, and comparing with the profit and loss level evaluation index is defined as the profit and loss level evaluation index comparison. do.

There is a comparison of profit and loss level evaluation indexes for aggregation and a comparison of component profit and loss level evaluation indexes.

First, the aggregation target comparison process will be described. The information generation unit 3021 calculates an evaluation index based on the aggregation target trading data, and compares the aggregation target with other aggregation targets, averages, and the like with the evaluation index. The comparison is to calculate various evaluation indexes from the aggregated trading data and compare the aggregated objects using the evaluation indexes obtained there.

There are comparisons based on technical indicators, performance indicators, etc., but by comparing the aggregated targets using the evaluation indicators obtained from the aggregated trading data, the differences in the trading status and holding status of the aggregated targets can be compared. It has the effect of clarifying.

(Specific example of aggregation target comparison process)
For example, if you compare how the profit / loss ratio of issue A is compared with the average value, you will be able to understand the situation of issue A well.

As shown in FIG. 48, for example, when the winning profit margins of the investor A and the investor B are compared as shown in (1) of FIG. 48, there is an effect that the difference between the buying and selling of the two becomes clear.

Investor A has a winning profit margin of 10%, and Investor B has a winning profit margin of 50%. Investor A has a short trading period of 20 days and is quick to make profits. On the other hand, it can be read that Investor B has a long trading period of 75 days on average, and profits are slowly taken large.

In addition, the winning percentage is 50% for Investor A, which means that he has repeatedly won and lost. It is an investment style that emphasizes the winning percentage by settingtle the settlement in a short period of time and settling profits and loss cuts quickly. On the other hand, although the winning rate of Investor B is as low as 30%, the profit margin at the time of winning is overwhelmingly high, and it can be seen that the loss rate of losing is suppressed.

The fact that there are many winning patterns 1 means a proactive investment, which is proof that the stock selection is correct. On the contrary, the reason why there are many winning patterns 3 is that the selection of the brand is wrong, and it seems that they are trying to cover it by buying and selling. In addition, as shown in FIG. 48 (1), Mr. B has a higher overall profit / loss ratio than the average, and profits are increasing.

The comparison of investment products for each aggregation target has a completely new effect by comparing the aggregation target with other aggregation targets, averages, etc. using the evaluation index obtained from the trading data. The targets of aggregation are stocks, stock groups, products, product groups, investors, investment types, and the like.

For example, it is possible to compare the unrealized profit / loss ratio between a product called virtual currency and an investment product called stocks. By comparing the aggregation targets with the evaluation index, there is an effect that the comparison becomes possible.

(Action of aggregation target comparison process)
The information generation unit 3021 calculates an evaluation index based on the trading data to be aggregated, and displays the comparison result of the aggregation target by using the evaluation index.

(Effect of aggregation target comparison process)
The situation can be compared from the comparison results of the aggregated objects using various evaluation indexes.

(Specific example of aggregation target comparison process)
For example, as shown in (2) of FIG. 48, it is an example to provide a comparative result that the trading profit / loss ratio of the A stock is higher than that of the B stock.

Stock A has a high unrealized profit / loss ratio, and many people who continue to hold it have recorded unrealized gains. On the other hand, it can be seen that there are many people who have recorded an unrealized loss with an unrealized profit / loss ratio of -5% for issue B, and many people have not obtained results even if they hold it for half a year. In particular, the unrealized gain ratio of issue A is very high at 70%, and it can be seen that an overwhelmingly high unrealized gain can be formed compared to those who have an unrealized loss of -10%. For those who give up stocks such as stock A early in short-term trading, it is also effective to choose to continue holding stocks by experiencing the high unrealized gains of those who continue to hold stocks. It will be an opportunity to change the way of.

Comparing the holding period of the person forming the unrealized gain with the holding period of the person forming the unrealized loss gives a clearer detail. As the level goes down (from the 2nd level to the 3rd level, etc.), more detailed information can be found, detailed comparisons can be made, and it becomes possible to compare the holding status and trading status of investors and stocks.

Of course, such comparison data between the A brand and the B brand is one of the article distribution data useful as an article. In this case, the article distribution data can be immediately utilized as article data by extracting the article distribution data from the database in the same process as the generation process.

(Definition of component comparison process)
Comparing with the evaluation index for each component obtained from the trading data to be aggregated is defined as the component comparison process. It is possible to make comparisons by component by comparing each component and target of aggregation based on various evaluation indexes calculated from the component trading data created by extracting and processing from the trading data to be aggregated. can.

(Issues in the component comparison process)
As shown in FIG. 49, in the comparison process, comparison for each aggregation target, comparison of evaluation indexes among investors, comparison of evaluation indexes between stocks, comparison for each period, and the like are performed. In the component comparison process, it is possible to compare the trading status (example of (2) in FIG. 49) and the holding status of Mr. A's A brand and B brand. It is also possible to compare Mr. A's 2019 and 2018, and the 2018 A brand and the 2019 B brand. It is also possible to compare the trading status of Mr. A's stock and virtual currency with the trading status of Mr. B's stock and virtual currency.

(Action of component comparison process)
The information generation unit 3021 creates the trading data to be aggregated, and creates the component trading data extracted and processed by the components. The information generation unit 3021 extracts, processes, and creates profit / loss level trading data from the component trading data, calculates a profit / loss level evaluation index based on the trading data, and calculates the evaluation index for each component to be aggregated. Compare. This allows the components to be compared.

(Specific example of component comparison process)
In the comparison process, comparison is performed for each aggregation target. Comparison of the evaluation indexes of Mr. A and Mr. B, comparison of the evaluation indexes of stocks A and B (example of (2) in FIG. 48), etc., but the information generation unit 3021 collects the trading data to be aggregated by Mr. A. , The component trading data of the A stock and the component trading data of the B stock are separately calculated to calculate the evaluation index ((2) in FIG. 49). For example, as shown in (1) of FIG. 49, the information generation unit 3021 divides the aggregated trading data of stock A into a component institutional investor group and a component individual investor group, and sets an evaluation index. calculate. As shown in the type classification of [Embodiment 3], comparison may be made for each type. The process of comparing each component with those calculated evaluation indexes is defined as the component comparison process.

(Effect of component comparison process)
By grasping the trading data from multiple perspectives such as trading data by investor and trading data by investment target, deeper analysis becomes possible. For example, it is possible to divide Mr. A's trading data to be aggregated into stock component trading data and virtual currency component trading data, calculate evaluation indexes for each, and compare them with the calculated evaluation indexes. This is just one example.

It is also a good example to compare Mr. A's trading data with the profit and loss level evaluation index between 2020 and 2019.

In addition, the trading data to be aggregated for stock A is divided into the investor type A, which has a strong short-term trading orientation, and the investor type B, which has a strong medium-term trading orientation, and the evaluation index is used. Calculation and comparison are good examples.

The aggregated trading data of Mr. A is divided into the component trading data of the A stock and the component trading data of the B stock, and compared. The aggregated trading data of stock A is divided into an institutional investor group, which is a component, and an individual investor group, which is a component, and evaluation indexes are calculated and compared.

Furthermore, by combining (1) in FIG. 49 with the investor table, the stock trading data to be aggregated can be divided into an institutional investor group, which is a component, and an individual investor group, which is a component, as an evaluation index. And compare it with the trading status of each of the above components of stock A. It is also possible to compare the components for each aggregation target in the component comparison process.

(Definition of profit / loss level evaluation index comparison process)
A profit / loss level evaluation index is calculated from the trading data to be aggregated, and the aggregation target or component is compared with other aggregation targets, other components, averages, etc. in the evaluation index. The comparison is to calculate a profit / loss level evaluation index from the aggregated trading data and compare the aggregated object or the component using the evaluation index obtained there. (Fig. 48 compares the trading data to be aggregated using the profit / loss level evaluation index)
(Issues in the profit / loss level evaluation index comparison process)
Comparison of aggregation targets includes comparison by technical indicators, performance indicators, etc., and the above comparison process. By comparing the aggregation targets and components using the profit and loss evaluation indicators by level obtained from the aggregation target trading data. It has a special effect by enabling multifaceted and multifaceted comparisons.

(Specific example of profit / loss level evaluation index comparison process)
For example, when comparing the profit and loss of the A issue and the B issue, the difference is further highlighted by comparing the profit and loss by level such as the total profit and loss level, the unrealized profit level, and the winning pattern level. When comparing the difference between Mr. A and Mr. B, and when comparing the difference between this month and last month, the difference is further highlighted (see FIG. 50 (4)).

Of these, of course, the data that can be used as article distribution data is the comparison data of issues A and B, and even if there is a difference between this month and last month, if it is data of all investors, it is also useful as article distribution data. ..

For example, comparing a stock that many people have unrealized losses with a stock that makes a lot of profits in short-term trading and clarifying the profit and loss has a great influence on how to buy and sell the stock. In this case as well, it can be mentioned as one of the data for article distribution. The same is true for some of the examples below.

For example, if you compare the unrealized profit / loss level of issue A with the profit / loss ratio of the trading profit / loss level compared to the average value, you will be able to understand the holding status and trading status of issue A.

For example, by comparing the average winning profit margin of the excellent stock group with the winning profit margin of the A stock belonging to the excellent stock group, the characteristics of the A stock are further clarified.

For example, there is an effect that the difference between the buying and selling and the holding of the two is clarified by comparing the winning profit ratio, the losing loss ratio, the unrealized profit / loss ratio, etc. of Investor A and Investor B.

For example, it is possible to compare the trading content and holding status of a product called virtual currency and an investment product called stocks. By comparing the aggregated objects with the profit and loss level evaluation index, there is an effect that more multifaceted and multi-layered comparison is possible. Furthermore, it is also possible to compare each component of the aggregation target and each component in the aggregation target.

As shown in FIGS. 48 to 50, the comparison of investment products by aggregation target or component is performed by using the profit and loss level evaluation index to compare the aggregation target and component with other aggregation targets, other components, averages, and the like. It has a completely new effect by comparing. For example, by comparing the unrealized loss rate, trading frequency, trading profit rate, etc., it becomes possible to better understand the trading status and holding status of the aggregation target and components.

(Effect of profit / loss level evaluation index comparison process)
The information generation unit 3021 calculates the profit / loss level evaluation index based on the aggregated trading data, and displays the comparison result of the aggregated object or the component using those evaluation indexes.

(Effect of profit / loss level evaluation index comparison process)
From the comparison results of the aggregated objects using various evaluation indexes of each profit and loss level, how the aggregated objects are handled in the market, what kind of state the current holders are, and how they are bought and sold. You can compare the situation such as whether you are there.

In addition, by comparing the aggregation target, the holding status of the component, and the trading status using the profit / loss level evaluation index, the status of the aggregation target and the component can be compared.

(Specific example of profit / loss level evaluation index comparison process)
For example, it is an example to provide a comparative result that the A stock has a higher trading profit margin, a higher unrealized profit margin, and a higher short-term trading profit margin than the B stock. In this case as well, it can be mentioned as one of the data for article distribution. This is because the information is needed by many investors.
"Mr. A has a higher trading profit margin than the average, a high unrealized profit margin, and a higher profit. In particular, the stock with a long holding period has an unrealized profit swelling, and the short-term trading profit margin is considerably higher than the average. A comparison is made for each investor, such as "."

The aggregation target comparison process, the component comparison process, and the profit / loss level comparison process have been described above. The effect of obtaining is shown.

(Issues of the first level comparison process)
There are comparisons based on technical indicators, performance indicators, etc., and the above comparisons, but in order to evaluate the total profit and loss, by further extracting the trading data to be aggregated and calculating the evaluation indicators. , Allows better comparisons for aggregated objects or components.

(Means of the first level comparison process)
The information generation unit 3021 calculates various evaluation indexes in order to evaluate the total profit / loss of the trading data to be aggregated, and compares the trading status holding status of the aggregation target or the component using those evaluation indexes. This solves the problem.

(Effect of first level comparison process)
By comparing the status of the aggregated object or component using various evaluation indicators of total profit and loss, how the aggregated object or component is handled in the market and how the total loss has occurred in the past year. , You can grasp the situation such as whether you are making a profit and how much the profit is. By comparing these evaluation indicators for each evaluation target or component, the characteristics of buying and selling of the aggregation target or component become clear, and the comparison results of various evaluation targets or components of the aggregation target or component are clarified. Become. It is possible to determine what kind of trading is being carried out for the aggregation target or component, and the holding status, trading status, etc. of the aggregation target or component.

(Specific example of the first level comparison process)
For example, the total profit / loss of the A stock is + 20% for the last six months, and the A stock can be understood more deeply by comparing it with the B stock using the average purchase unit price, average profit amount, purchase amount, etc. be able to. In this case as well, it can be mentioned as one of the data for article distribution. This is because the information is needed by many investors. If it is an article such as what is the difference between buying and selling S1 company stock and S2 company stock, the value will be greatly increased.

For example, the B stock has a total profit / loss of -5%, and the average purchase unit price and the average loss amount are compared. By comparing at the total profit / loss level, it is possible to compare what kind of total profit / loss is brought about as a result of buying / selling or holding the aggregated object or component. Since the total profit / loss includes both the trading data held and the trading data, the total profit / loss status of the aggregated object or component is grasped, and the evaluation index is calculated and compared. It is possible to grasp the whole picture of buying and selling of components.

(Second level comparison process)
The evaluation index used at the trading profit / loss level includes the trading profit / loss ratio, the purchase price, the selling price, the trading average period, the average buying price, the average selling price, the trading volume, and the winning percentage.

(Issues of the second level comparison process)
In the comparison of the total profit and loss of the aggregated target or component of the investment product, the fixed profit bought and sold and the undetermined profit are included, so only the total comparison can be made. The comparison results obtained from the evaluation index for trading profit and loss are the winning rate, trading profit and loss ratio, trading period, etc., which were not known from the total profit and loss, as well as what kind of buying and selling, average buying price, selling price, etc., and what kind of result is You can compare whether it came out.

(Means of the second level comparison process)
The information generation unit 3021 calculates various evaluation indexes in order to evaluate the trading profit / loss of the trading data aggregated for each aggregation target or component, and uses those evaluation indexes to evaluate the aggregation target or component. Compare the trading status.

(Effect of second level comparison process)
By comparing the status of the aggregated object or component using various evaluation indexes of trading profit and loss, how the aggregated object or component is handled in the market The trading status such as average rate of return and holding period I understand. By comparing these evaluation indicators for each evaluation target or component, the characteristics of buying and selling of the aggregation target or component become clear, and the comparison results of the various evaluation targets or components of the aggregation target or component are clarified. Become. It is possible to determine what kind of trading character the aggregation target or component has.

(Specific example of the second level comparison process)
To give a specific example, the A stock has a trading profit / loss ratio of 5%, but the average holding period is one week and the turning power is high, and the winning rate is 60%. On the other hand, the B stock has a trading profit / loss ratio of -5%, an average holding period of 3 weeks, and a winning rate of 40%. Comparisons for each issue and each evaluation index are made at the trading profit level. In order to compare from the trading data, it is possible to grasp the trading status of the stock, and it is possible to compare the stock with a strong short-term trading orientation and the stock with a long holding period in the medium to long term, for short-term trading. It will be possible to know which stocks are suitable and which stocks are suitable for medium- to long-term holding through comparison results. In this case as well, it can be mentioned as one of the data for article distribution. This is because the information is needed by many investors.

(Issues in the second level (unrealized gain / loss) comparison process)
At the total profit / loss level, the holding status and trading status are not known in detail because the holding status and the trading status are mixed. Evaluating the unrealized gain / loss level reveals the unrealized gain / loss ratio, average holding period, average bid price, average profit amount, and so on.

(Means of the second level comparison process)
The information generation unit 3021 calculates various evaluation indexes in order to evaluate the unrealized profit / loss of the unreversed trading data aggregated for each aggregation target or component, and uses those evaluation indexes to calculate the aggregation target or configuration. Compare the possession status of the elements.

(Effect of second level comparison process)
By comparing the holding status of the aggregated object or component using various evaluation indexes of unrealized profit and loss, it is possible to understand the holding status of the owner of the aggregated object or component. .. For example, the following comparisons are possible.

Stock A has an average unrealized gain ratio of 50% (1.5 times), while stock B has an average unrealized loss ratio of 5%, which can be compared with a small one, and the holding period is the former. Is one year, and the latter is half a year on average, which makes it possible to compare various evaluation indexes at the second level. At this unrealized gain / loss level, it is possible to compare the status of holding the aggregated object or component.

(Issues in the second level (linked unrealized gain / loss) comparison process)
The above unrealized profit / loss comparison process is not linked to trading profit / loss, but compares unrealized profit / loss separately. However, in reality, unrealized gains / losses are formed in conjunction with past realized gains / losses, taking into account compound interest effects, leverage effects, and the like. Adding linked items to the comparison items creates a linked unrealized profit and loss comparison process that enables even higher-level comparisons.

(Means of the second level (linked unrealized profit / loss level) comparison process)
The information generation unit 3021 adds interlocking items to the unrealized profit / loss level comparison process and compares them.

(Effect of the second level (linked unrealized profit / loss level) comparison process)
For example, the question of what to do with the valuation of those who have made a lot of profits in the past and now have a valuation loss, and those who have made a big loss in the past but now have a lot of unrealized profits. There is.

If you simply evaluate at the unrealized profit / loss level, the latter works well, and the former has a lower evaluation. However, in reality, if the former is in a state where it has made a lot of profits from the principal and the unrealized profit and loss formation funds have increased sufficiently, the current evaluation must be high. On the contrary, if the latter is a little less than the principal and the condition is improved a little, the result will be inferior to the former.

Since the unrealized gain / loss is not disjointed with the past trading gain / loss but is linked, it is possible to make a comparison with a higher level of the linked unrealized gain / loss level comparison.

(Significance of the 3rd level comparison process (comparison of winning profit level evaluation indicators))
In the third level comparison, the information generation unit 3021 calculates evaluation indexes at the winning trade and losing trade (evaluating the winning profit and the losing loss separately from the traded data), and calculates those evaluation indexes. Compare by aggregation target or component.

(Issues of the third level comparison process)
At the second level of trading profit / loss and unrealized profit / loss levels, there is a mixture of wins and losses, so there is an important element for comparing the winning profit margin and the losing loss ratio.
(Means of the third level comparison process)
The information generation unit 3021 calculates various evaluation indexes for evaluating trading profits and trading losses from trading data aggregated for each aggregation target or component, and uses those evaluation indexes to calculate the aggregation target or component. Compare the trading status of.

(Effect of 3rd level comparison process)
Since the trading status is compared by calculating the winning profit rate, losing loss rate, etc. of the aggregated object or component using various evaluation indexes such as trading profit and trading loss, the aggregated object or component wins. You can see how much profit will increase if you lose, and how much loss will be suppressed if you lose.

(Specific example of the third level comparison process)
For example, regarding the winning trade of stock A, the average buying price is 4000 yen, the average selling price is 4500 yen, the average profit margin is 12%, and the average holding period is 2 weeks. On the other hand, regarding the losing trade of stock A, the average buying price is 4800 yen, the average selling price is 4500 yen, the average loss rate is -8%, and the average holding period is 5 days. In this case as well, if it is the number of all A stocks, it can be listed as one of the data for article distribution. This is because the information is needed by many investors. On the other hand, in the case of A stocks of a specific investor named Mr. A, it is useful information for solving problems that improve the investment results of Mr. A.

The server 30 causes the display unit 23 of the terminal 2 to display such a comparison result. The information generation unit 3021 separately extracts the winning trade and the losing trade from the traded data, calculates each evaluation index, and compares using those evaluation indexes. This enables a deeper evaluation based on the profit rate of winning trades and the loss rate of losing trades of each stock, and the trading situation can be understood in more detail.

(Significance of the comparison process of the third level (unrealized gain level evaluation index and unrealized loss level evaluation index))
The information generation unit 3021 calculates the evaluation index separately for the unrealized loss level and the unrealized gain level, and compares the evaluation indexes.

(Third level (unrealized gain and unrealized loss) issues in the comparison process)
At the second level of trading profit and loss and unrealized profit and loss levels, there are both wins and losses in unrealized gains and losses, so there is no important element for comparison of unrealized gains and losses, unrealized loss ratios, and holding periods of each. There is.

(Third level (unrealized gain and unrealized loss) means of comparison process)
The information generation unit 3021 calculates various evaluation indexes in order to evaluate the unrealized loss and unrealized gain of the trading data aggregated for each aggregation target or component, and uses those evaluation indexes to evaluate the aggregation target or component. Compare the holding status of.

(Effect of the third level (unrealized gain and unrealized loss) comparison process)
The holding status can be compared by calculating the unrealized loss ratio and unrealized gain ratio of the aggregated object or component using various evaluation indexes such as unrealized gain and unrealized loss. You can see how much the unrealized gain of the subject or component has increased and how much the unrealized loss has been suppressed.

(Specific example of the third level (unrealized gain and unrealized loss) comparison process)
For example, among the holders of stock A, 80% of the holders record unrealized profits, and the average unrealized profit ratio is 70%. On the other hand, among the holders of stock B, only 20% of the holders have unrealized profits, and the unrealized profit ratio is 10%. Such comparison results can be provided to the user.

Among the holders of stock A, 20% of the holders have unrealized losses, and the unrealized loss ratio is suppressed to -10%. On the other hand, those who still have unrealized losses on stock B account for 80% of the holders, and the unrealized loss ratio is -3%. In this way, it is possible to grasp the purchase status and unrealized profit / loss status of the stocks held, and obtain comparative results such as how many people have unrealized gains. In this case as well, if the numbers are for the A stock and the B stock as a whole, they can be listed as one of the data for article distribution. This is because the information is needed by many investors. In fact, it will be a very valuable article as an article because you can see the actual situation of which brand is profitable for many people. For example, if we can find out that the stocks that are popular with individual investors actually have unrealized losses, we will not be able to do anything, so this is socially necessary news.

(Significance of the comparison process of the third level (linked unrealized gain level evaluation index and linked unrealized loss level evaluation index))
The information generation unit 3021 separately compares the linked unrealized loss level evaluation index and the linked unrealized gain level evaluation index.

(Third level (linked unrealized gain and linked unrealized loss) Issues in the comparison process)
By adding linked items to the comparison of unrealized gain levels, the unrealized gain formation funds of the Omoto where unrealized gains are formed will also be evaluated, and comparisons linked to trading profits and losses will be possible, and the leverage effect and compound interest effect will be possible. You can compare the important effects of investment products such as.

(Third level (linked unrealized gain and linked unrealized loss) means of comparison process)
The information generation unit 3021 adds interlocking items to the unrealized gain level comparison process and the unrealized loss level comparison process and compares them.

(Effect of the third level (linked unrealized gain and linked unrealized loss) comparison process)
The information generation unit 3021 calculates the linked unrealized gain level evaluation index and the linked unrealized loss level evaluation index from the linked unrealized gain level trading data and the linked unrealized loss level trading data, and compares them using the evaluation indexes.

For example, the question is what to do with the evaluation of people who have made a lot of profits in the past and now have a little unrealized profit, and those who have made a big loss in the past but now have a lot of unrealized profit. be.

If you simply evaluate at the unrealized gain level, the latter works well, and the former has a lower evaluation. However, in reality, with regard to the former, the current evaluation must be high if it is in a state where a large amount of profit is made from the principal and the unrealized profit formation fund is sufficiently increased. On the other hand, with regard to the latter, if the principal is significantly interrupted and the situation seems to have improved a little and the unrealized gain formation funds are small, the result will be inferior to the former.

Since the unrealized gain is linked to the past trading profit and loss rather than separately, it enables a higher level comparison of the linked unrealized gain level comparison.

(Specific example of the third level (linked unrealized gain and linked unrealized loss) comparison process)
For example, among the holders of stock A, 80% of the holders record unrealized profit formation funds, the average unrealized profit ratio is 70%, and the average trading profit ratio is 20%. Because it is expensive, many investors are doing well both in buying and selling and holding.

On the other hand, among the holders of stock B, only 20% of the holders have unrealized gains, the unrealized gain ratio is 10%, and the trading profit / loss is also negative.

Such comparison results can be provided to the user.

(4th level comparison process (meaning of comparison of winning pattern level evaluation index)
The information generation unit 3021 makes a comparison at the fourth level of the profit / loss level by using the winning pattern analysis and the losing pattern analysis having different personalities even if they have the same winning trade and the same losing trade.

(Issues of the 4th level comparison process)
A fairly detailed holding status and trading status can be grasped by comparing the investment product aggregation target or the winning profit margin for each component, but by further comparing with the market price after selling, a more detailed comparison becomes possible. ..

(Means of the 4th level comparison process)
The information generation unit 3021 calculates various evaluation indexes from the aggregated trading data in order to evaluate the winning pattern and the losing pattern, and compares the trading status of the aggregated object or the component using the evaluation indexes. ..

(Effect of 4th level comparison process)
By comparing the winning pattern, losing pattern, etc. of the aggregated object or component using various evaluation indexes of trading profit and loss, what kind of movement is made after the aggregated object or component is sold? You can compare buying and selling, such as whether or not the answer was correct.

(Specific example of the 4th level comparison process)
For example, with regard to stock A, buying and selling of winning pattern 1 (buying price <selling price <current price) accounts for 80%, the remaining 10% is pattern 2, 10% is pattern 3, and the ratio of pattern 1 is very high. , It is possible to display the comparison result that stable trading profit can be obtained. Pattern 1 is "buy price <sell price <current price", and if the winning pattern of pattern 1 has a high weight, it can be said that stable short-term trading is easy. In this case as well, if it is the number of all A stocks, it can be listed as one of the data for article distribution. This is because the information is needed by many investors. Articles such as "This is the brand that is easy to trade in the short term!" Will be a high-profile article.

In particular, a stock with a high winning profit margin in winning pattern 1 can be said to be a short-term trading flower-shaped stock. On the other hand, in the pattern analysis of B stocks, the losing pattern occupies most, and the pattern of "buying price> selling price> current price" which is the losing pattern 3 occupies 80% of the losing pattern, and those who are losing trades. It is a very large number of stocks. In this way, comparison results and the like can be expressed.

I sold it with a loss cut immediately after I bought it, but the loss rate is suppressed to minus 2%, and I can display the comparison result that the stocks that are frequently loss cut with the losing pattern 3 but the loss is suppressed. ..

(4th level (Unrealized gain / loss pattern analysis) Significance of comparison process)
At the fourth level of the profit / loss level, the information generation unit 3021 makes a diagnosis by comparing the unrealized gain rate with different characteristics and the benchmark increase rate, the unrealized loss rate and the benchmark decrease rate, and the like.

(4th level (Unrealized gain / loss pattern analysis) Diagnostic process issues)
A fairly detailed holding status can be grasped by diagnosing the aggregation target and the unrealized gain rate for each component, but by further comparing the benchmark decline rate, increase rate, unrealized gain rate, and unrealized loss rate, a more detailed comparison becomes possible.

(4th level (unrealized gain / loss pattern analysis) means of comparison process)
The information generation unit 3021 calculates various evaluation indexes in order to evaluate the unrealized loss rate and the unrealized gain rate of the aggregated trading data, and compares the possession status of the aggregated object or the component using those evaluation indexes. ..

(Effect of 4th level (unrealized profit / loss pattern analysis) comparison process)
By comparing the status of unrealized gains and unrealized losses of the aggregated object or component using various evaluation indicators of unrealized loss and unrealized gain, how the aggregated object or component is moving compared to the average. , You can compare the holding status such as whether you have the correct answer.

(4th level (unrealized gain / loss pattern analysis) means of comparison process)
The information generation unit 3021 calculates various evaluation indexes in order to evaluate the unrealized loss and unrealized gain of the aggregated retained data, and diagnoses the possession status of the aggregated object or component using the evaluation indexes.

(4th level (Unrealized gain / loss pattern analysis) Effect of diagnostic process)
By comparing the status of the aggregation target or component using various evaluation indexes such as unrealized loss and unrealized gain, the holding status of the aggregation target or component can be understood. On the other hand, whether the unrealized gain is the rate of increase of the stocks held above the benchmark or below the benchmark has a big difference in meaning even if the unrealized gain is the same. Therefore, the stocks that form an unrealized loss are rated low.

(Specific example of the 4th level (unrealized profit / loss pattern analysis) comparison process)
For example, with regard to stock A, the unrealized gain is held at a return that greatly exceeds the Nikkei average, the benchmark surpass rate is 50%, and the holding and purchase of stock A has resulted in a result that exceeds the Nikkei average. On the other hand, in the pattern analysis of the unrealized gain / loss of the B stock, it has an unrealized loss and records a loss below the Nikkei average, the benchmark lowering rate is 1%, the rate of decline is almost the same as the Nikkei average, and there is little taste even if it is held. It can be said that it is a brand. Even if the stocks are higher than the benchmark, what kind of stocks are higher than the benchmark, and the stocks that are significantly lower than the benchmark should be reviewed.

(Specific example of comparison process)
(Specific example 1)
Comparing the evaluation indexes of day trading type and swing trading type by investment type is an example. In this case as well, it can be cited as one of the data candidates for article distribution. This is because the information is needed by many investors. On the other hand, in the case of A stocks of a specific investor named "Mr. A", it is useful information for solving the problem of improving Mr. A's investment results.

(Specific example 2)
One example is the comparison of evaluation indicators between stocks that are making trading profits and stocks that have trading losses recorded in the investment type = day trading type. In this case as well, it can be mentioned as one of the data for article distribution. This is because the information is needed by many investors. On the other hand, in the case of A stocks of a specific investor named "Mr. A", it is useful information for solving the problem of improving Mr. A's investment results.

(Specific example 3)
One example is to compare the trading frequency and winning rate of the day trading type with the trading frequency and winning rate of the medium- to long-term holding type, with the issue = A brand as the extraction condition. In this case as well, if it is the number of all A stocks, it can be listed as one of the data for article distribution. This is because the information is needed by many investors.

(Specific example 4)
Extraction condition is brand = A brand, and the component is technical index = trading data with RSI of 50% or more at the time of purchase is compared with trading data of 50% or less, and which evaluation index is superior, etc. , Is an example. In this case as well, if it is the number of all A stocks, it can be listed as one of the data for article distribution. This is because the information is needed by many investors.

(Specific example 5)
It is also possible to compare the trading data of stock type = trader stock with the trading data of stock type = excellent stock, and calculate and compare the evaluation index by the information processing system. This is just one example. In this case as well, it can be mentioned as one of the data for article distribution. This is because the information is needed by many investors.

(Specific example 6)
Based on the trading data to be aggregated by period in 2020 and 2019, it is possible to compare the trading data and the evaluation index with the classification standard = A issue, and compare how much the result of A issue changed depending on the period. Become. In this case as well, if it is the number of all A stocks, it can be listed as one of the data for article distribution. This is because the information is needed by many investors.

The display step of how to display such information may be incorporated into the comparison process, or may be summarized in the eleventh step. In this case, for example, in the example of Specific Example 6, information indicating the trading result of 2020 and the trading result of 2019 is generated by the information processing system in the information of the A brand, or the A brand is held. "I would like to inform you about the investment results of A stock in 2020. The average trading profit / loss ratio and win rate of A stock in 2019 and 2020 were 30% and 70% in 2019, respectively, but it was good. It is also an example that the information processing system generates text information such as "Everyone is depressed in 2020, and it is depressed to -10% and 15%, respectively."

This comparison process is performed as follows. For example, Investor A will explain what steps to take when he wants to find out how his investment results are compared to the average. Investor A's aggregated trading data and investor average aggregated trading data are created. As the next step, create the total profit and loss level trading data for each. As the next step, the information processing system calculates an evaluation index that affects each total profit and loss. Here, there is a step to determine more accurateness by weighting the evaluation index and comparing it with which evaluation index. Then, a table comparing the investor A and the investor average is created with the evaluation index, and is displayed through the display steps. In one of these steps, there is the question of how to determine which evaluation index is appropriate to compare with the weighting of the evaluation index.

A large number of evaluation indexes are calculated by the information processing system for the weighting of the evaluation indexes and the step of determining which evaluation index is appropriate to compare. If it is the total profit / loss level, it varies from the turnover index to the trading profit / loss, the number of trading times, the winning profit rate, the losing loss rate, the unrealized profit rate, the unrealized loss rate, and the like. However, the total profit / loss has a structure of = trading profit / loss (= winning profit + losing loss) + unrealized profit / loss (unrealized profit + unrealized loss). Profit and loss is less important. However, when the difference and deviation rate (with the average) compared to the average are calculated by the information processing system, some numbers are higher than the average and some are lower than the average. There are ways to exceed that (evaluation index with a large divergence rate) and evaluation indexes with a low divergence rate. In this case, when comparing with the average, the weighting of the upper layer is increased, the weighting of the evaluation index with a large deviation rate from the average is increased, conversely, the weighting is decreased for the lower layer, and the weighting is applied to the index with a low deviation rate. By reducing the number, it is possible to judge which evaluation index should be compared to display more accurately.

By incorporating this step (evaluation index judgment step), it is possible to solve which evaluation index should be compared among many evaluation indexes so that it can be displayed in an easy-to-understand manner.

(Definition of comparison by trading data by component with the investment target as the component of the trading data to be aggregated by investment target)
To give an example of comparison using the information processing system using the trading data by component with the investment target of the trading data to be aggregated by investment target as a component, the buying and selling of A stock and the buying and selling of B stock among the stocks are , Comparison using evaluation indicators such as trading profit / loss ratio and unrealized profit / loss ratio. An example is the case where ~ (investment target) is compared by ~ (investment target) using an evaluation index (calculated by the information processing system under the relevant conditions). Among the stocks, comparing the A stock with the B stock by the total profit / loss ratio by the information processing system, or comparing the stocks by the trading profit / loss ratio or the winning percentage by the stock in the information processing system is one specific example. be.

(The effect of comparison by trading data by component with the investment target as the component of the trading data to be aggregated by investment target)
Based on the trading data to be aggregated, the information processing system processes the investment target under the conditions such as extraction conditions, classification conditions, aggregation rules, etc., and further extracts, classifies, or aggregates by investment target, and further processes at the profit / loss level. Based on the trading data, the evaluation index calculated by the information processing system is used for comparison. This makes it possible to compare the trading data for each component, which has the investment target as the component, in the information processing system. The comparison target may be a comparison of trading data between the A stock and the B stock in the stock, or the stock may be compared by the winning percentage for each stock.

(Effect of comparison by trading data by component with the investment target as the component of the trading data to be aggregated by investment target)
The comparison is based on the actual trading data of the stocks by the information processing system, and has the effect of enabling multifaceted comparisons that cannot be compared with the usual stock comparisons. For example, among the stocks, the A stocks held have a low win rate of 15% (average 49%) in September compared to the average, and quite everyone is struggling. Expression is possible. It can be said that the content is unique to comparison based on the trading data by component, which is the trading data to be aggregated by investment target, and the trading data to be aggregated by investment target by the information processing system.

(Specific example of comparison by trading data by component with the investment target as the component of the trading data to be aggregated by investment target)
Among the stocks, the evaluation indexes of the stock group and the excellent stock group are compared, the trading profit / loss ratio, the winning rate, the winning profit rate, the unrealized loss rate, etc. are calculated by the relevant information processing system, and the comparison result is displayed. Is one of the concrete examples.

(Definition of comparison based on trading data by component with investors as components of trading data to be aggregated by investment target)
To give an example of comparison using the trading data by component with the investor as the component of the trading data to be aggregated by investment target, the trading of Mr. A and the trading of Mr. B in the trading of A brand can be performed by the information processing system. Comparisons can be made using evaluation indicators such as the calculated trading profit / loss ratio and unrealized profit / loss ratio. ~ (Investment target) ~ (Investor) In some cases, the evaluation index (calculated by the information processing system under the relevant conditions) is compared by the information processing system. When buying and selling stocks, comparing the total profit / loss ratio between Mr. A and Mr. B with the information system, and comparing stocks with the information system for each investor by the trading profit / loss ratio and winning rate are one concrete example. This is an example.

(The effect of comparison of trading data by component with investors as components of trading data to be aggregated by investment target)
Based on the trading data to be aggregated, the information system narrows down the investment targets by extraction conditions, classification conditions, aggregation rules, etc., and further extracts, classifies, or aggregates the trading data by investor. Based on the target trading data further processed at the profit / loss level, comparison is performed using the evaluation index calculated by the information processing system. This makes it possible to compare the trading data by component, which has the investor as the component, of the trading data to be aggregated by investment target. The comparison target may be a comparison of trading data between Mr. A in the buying and selling of stocks and the average, or the stocks may be compared by the winning percentage for each investor.

(Effect of comparison of trading data by component with investors as components of trading data to be aggregated by investment target)
The comparison is based on the actual trading data of the stock by the information processing system, and has the effect of enabling a concrete and unprecedented comparison. For example, in the buying and selling of stocks in 2020, it is possible to express such as "Mr. A has a higher evaluation index than the average and is inferior to this evaluation index".

(Specific example of comparison by trading data by component with investors as components of trading data to be aggregated by investment target)
Comparing the evaluation indexes of the investor group with excellent performance and the investor group with poor performance, the trading profit / loss ratio, winning rate, winning profit rate, unrealized loss rate, etc. are calculated by the relevant information processing system and the comparison result is displayed. Is one of the concrete examples.

It is possible to compare the evaluation indexes for the following periods in the same manner as in the above specific example.

(Specific example 3 of comparison by period)
It is possible to compare the evaluation index of the AB period and the evaluation index of the CD period with respect to the investment target A stock by the same procedure as the above specific example.

(Specific example 4 of comparison by period)
It is possible to compare the evaluation index of the investment target A issue with the AB period evaluation index and the investment target B issue with the AB period evaluation index by the same procedure as the above specific example.

(Significance of ranking process)
The information generation unit 3021 calculates a profit / loss level evaluation index from the aggregated trading data and ranks it based on the profit / loss level evaluation index. The ranking process is to calculate a profit / loss level evaluation index from the aggregated trading data by the information processing system and rank using the profit / loss level evaluation index obtained there. The ranking process is divided into component ranking, aggregation target ranking, and multi-layered ranking, depending on what is ranked. In addition, the ranking process is from the first level to the fourth level depending on the type of the profit / loss level evaluation index used as the standard for ranking.

(Definition of ranking step)
The first step is the acquisition step of trading data. It is also the trading data creation phase. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component. The fourth step is the step of creating profit / loss level trading data. The fifth step is the calculation and selection step of the evaluation index by the information processing system. The operation phase is a phase of "what to do" using the evaluation index extracted and selected in the fifth step, and the order relationship with other steps does not matter.

The sixth step is an evaluation step. The seventh step is a comparison step. The eighth step (this step) is to rank different aggregation targets or components based on the evaluation index (single or multiple) calculated by the information processing system. Defined as a ranking process.

(Issues in the ranking process)
For investors, what is their ranking, what is their trading profit and loss, what is the rate of increase in valuation relative to the principal, what is the stock, and what is the virtual currency? It is currently difficult to know the ranking status such as. Also, as for news distribution, what was the actual trading situation this month, whether all the actual trading conditions this year are profitable or losing, etc. do not appear in the world. When it comes to stock information, we are paying close attention to stock information and business performance trends. There is little information distribution based on actual sales, and there are gaps in information such as personal blog distribution, which often lacks accuracy or is a partial view.

(Action of ranking process)
Ranking is facilitated by following the process as shown in the definition of ranking process. When ranking the trading profit and loss of Mr. A for each year, the component trading data is used, so the component ranking is suitable. When ranking the total profit and loss of Mr. A's stock among investors, the trading data to be aggregated is ranked. Decide whether to use the aggregation target ranking process or the component ranking process depending on what index is ranked in which target. In order to make a multifaceted ranking of investors, it is possible to rank multiple evaluation indexes of Mr. A in the trading data to be aggregated, and the success rate (win rate) in the actual trading of stocks is subject to aggregation. This is possible by creating trading data for each issue using component trading data, and ranking the issues based on the winning rate using the winning rate as an evaluation index in the trading data.

It can also be used for an automatic article distribution system. For example, the relevant information processing system for articles such as the trading profit margin ranking of stocks in 2020, the current unrealized profit margin ranking, the trading profit ranking due to the upward revision in 2020, the stock ranking purchased today, the stock ranking earned the most this week, etc. It can also be automatically generated by. The second step, the third step, the fourth step, and the fifth step are updated daily if the data can be created with newly updated updated data under the same conditions. Such information can be acquired at any time by being stored in the sequential storage unit 33 every day, and can be used for comparison with past data and graphs of time-series data.

(Effect of ranking process)
In this ranking process, various targets can be ranked using various evaluation indexes, and for users, it is a guide for how to raise the ranking and how to improve it. Also, as a news article, it has the effect of making it possible to understand whether stocks that have not appeared in the world are really profitable, and how much the people who are losing are losing. be.

(Specific example of ranking process)
Ranking of trading profit and loss of Mr. A, annual ranking of winning profit of Mr. A, trading frequency ranking of securities companies, ranking of trading profit and loss ratio based on advice from adviser a, which medium is the best to refer to in 2020 It can be considered from various viewpoints such as the winning profit margin ranking to know whether the winning profit margin was high and the winning percentage ranking of the stock in 2020. In this case as well, if it is the total number, let's give it as one of the data for article distribution. This is because the information that many investors need. As shown below, rankings, component rankings, multi-layered rankings, etc. are used properly for each aggregation target, depending on which evaluation index is ranked in which target and which target ranking is presented. If it is an investor's ranking, the ranking for each aggregation target is suitable, the annual ranking of investor A is suitable for the component ranking, the multi-layered ranking is the ranking by stock that Mr. A has an unrealized loss, and profits are often generated in short-term trading. It can be said that the stock rankings that are available are suitable.

In addition, as articles that are likely to be of interest, technical chart success rate ranking, stock loss ranking, this month's profit margin top stock ranking, people who lost in this news (unrealized loss rate) ranking, people who got in this news (unrealized profit rate) ) Ranking etc. Articles with high news characteristics include the 2020 win rate ranking, this month's trading profit rate ranking, and so on. All of these articles can be generated using the ranking process.

As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated, and an evaluation index according to the purpose is calculated. Therefore, even in this step, various conditions and various forms of evaluation indexes can be easily ranked and displayed. Although this step is only one step in FIG. 102, since the evaluation indexes have been determined by a series of cooperation, the rankings of the evaluation indexes of many forms and the rankings of many targets mentioned in the present specification are. It is possible.

(Definition and type of evaluation index ranking)
The ranking is defined as the evaluation index ranking, which is obtained by calculating various calculated evaluation indexes for each investor or investment target, rearranging the evaluation indexes, and ranking them.

(Conventional issue)
Regarding stocks, which are one of the investment targets, various rankings such as market capitalization ranking, trading value ranking, PER ranking, and ordinary profit growth rate ranking can be mentioned. However, these rankings are not linked to actual trading data. It is completely different from ranking the evaluation index calculated from the actual trading data.

(Issues of evaluation index ranking)
For example, there are various rankings related to investment targets as described above, but since they are not linked to actual trading data, it is unknown how the performance of those who purchased stocks with low PER is. As for the ranking of investors, if there is a ranking based on actual trading data, you can know your position and average, and it will be a guide for how to improve.

(Effect of evaluation index ranking)
There are as many evaluation index rankings as there are evaluation indexes. The types include investor ranking based on the evaluation index of trading data (transaction data) in a narrow sense, and investment target ranking based on the performance evaluation index of the investment target and the evaluation index of the technical index of the investment target.

Investor rankings can be created by deciding evaluation indicators to be ranked, calculating for each investor, and ranking them. An investment target ranking can be created by calculating and ranking each investment target.

(Effect of evaluation index ranking)
It will be possible to see the average image of investors, the methods of top-level investors, their position and points to be improved, which has the effect of greatly contributing to the improvement of investors' investment behavior. You can expect it. The investment target ranking greatly contributes to the selection of investment targets and the decision to buy or sell investment targets. The stocks that have risen sharply for a moment and have moved flashily can be expected to have the effect of clarifying the fact that most people actually have big losses.

(Specific example of evaluation index ranking)
A specific example of the evaluation index ranking will be described below.
(1) Ranking of rate of increase / decrease during the holding period (2) Ranking of trading data evaluation index (total profit / loss ratio) in a narrow sense (3) Ranking of revision rate of earnings forecast (4) Ranking of technical index (Definition of ranking of rate of increase / decrease during the holding period)
When the purchase time of the investment target product is A time point, the sale time point (or the current time during the holding period) is B time point, and the evaluation price at that time point is the A time point price and the B time point price, the price of the investment target product rises and falls. The rate can be expressed by the B time point price / A time point price.

The information generation unit 3021 calculates the B time point price and the A time point price of the investment target product and the alternative investment target product, ranks them based on the B time point price / A time point price, and raises or lowers the investment target product. Find the rate ranking. This is defined as the rate of increase / decrease ranking during the holding period.

(Previous technology)
We often see monthly ups and downs and daily ups and downs. However, the most important thing for investors is that the funds are bound by the target product during the holding period of the target product. Therefore, in order to judge whether or not it is okay to select the investment target product during the holding period, the ranking of the rate of increase / decrease during the holding period is important.

If it is higher in the rate of increase / decrease ranking, it means that the target product was selected well, and if it is lower in the rate of increase / decrease ranking, it means that better performance was obtained if a more appropriate selection was made. means.

(Issues in ranking the rate of increase / decrease during the holding period)
The rate of increase / decrease ranking is mainly monthly (weekly, daily) increase rate rankings. For example, if you purchase a brand A with cash of 500,000 yen, how much it has increased from the date of purchase, and purchase other brands. It is important to know how it would have been if it had been, compared to the stocks with the highest or average rate of increase.

(Effect of rising / falling rate ranking during the holding period)
By determining the time points A and B, the rate of increase / decrease of the investment target product is determined, and the rate of increase / decrease of the substitutable investment target product (close price, closing price, etc.) is also determined, so that the rate of increase / decrease ranking becomes possible. The definition of substitutable investment target products can be limited to stocks, the first section of the Tokyo Stock Exchange, the minimum purchase price, and various other restrictions.

(Effect of rate of increase / decrease during the holding period)
A special effect can be expected, in which it is possible to verify whether or not the selection from a number of investment targets was correct. For example, the position of one's own selection skill is clarified by comparison with the average value, comparison with the highest ranking, and the number of stocks.

(Specific example of the rate of increase / decrease during the holding period)
If the stock price and date are decided, it is OK.

For example, taking Company F as an example, from 829 yen on September 10, 2020 to 2060 yen on February 17, 2021, the rate of increase / decrease is 2.48 times and the RSI is 50%. From September 10, 2020 to February 17, 2021, the information generation unit 3021 obtains the top 10 of the rate of increase / decrease, NO1, and the average. Then, Company F tells the user what number it is. Furthermore, the NO1 brand tells which brand and how many times the rate of increase / decrease is.

(Definition of total profit / loss ratio (transaction data evaluation index) ranking)
When evaluating the total profit / loss ratio of A investor during the AB period, it is comprehensive to show the ranking and the number of people compared to the total profit / loss ratio of other investors during the same period. Defined as profit / loss ratio ranking. Similarly, in the case of the trading profit / loss ratio, it is defined as the trading profit / loss ratio ranking. Similar rankings can be defined for any metric obtained from transaction data.

(Previous technology)
Even if the results of Investor A during the AB period can be grasped, the fact is that there is no way to know the position of the investor A in the whole and what the other investors are like.

(Comprehensive profit / loss ratio (transaction data evaluation index) ranking issues)
Even if you can compare your own achievements and the market as a whole (for example, the Nikkei 225), there is no way to know how it was compared to other investors, which is why investors are rumors and hoax information. Being deceived, I have a loss before I know it. It is a big challenge for all investors to know their position by comparing and ranking their average appearance and the achievements of excellent investors with their own achievements, and to be able to find a way to improve. Is.

(Effect of total profit / loss ratio (transaction data evaluation index) ranking)
First, determine the AB period. In the case of the total profit / loss ratio ranking, the total profit / loss ratio is calculated from the trading data of investor A by period in the AB period, or the valuation amount at the time A and the valuation amount at the time B are calculated (the valuation amount at the time B). -The total profit / loss ratio is calculated by the evaluation amount at the time of A) / the evaluation amount at the time of A (the case of deposit / withdrawal = 0). Ranking data can be obtained by calculating the total profit / loss ratio and ranking by other investors in the same procedure. Considering that other evaluation indicators such as other trading profit / loss ratios can be easily calculated, the former calculation is desirable.

(Effect of total profit / loss ratio (transaction data evaluation index) ranking)
In the case of the total profit / loss ratio ranking, by ranking the total profit / loss ratio during the AB period, what is the overall position of oneself, how much achievement is the first person, and what is the average? You will be able to understand the results such as whether it is lower or higher than the average.

(Specific example of total profit / loss ratio (transaction data evaluation index) ranking)
For example, from September 10, 2020 to February 17, 2021, it is possible to compare their own achievements by telling them how well the investor's total profit and loss ratio NO1 and top 10 are. It is possible to compare the performance obtained by buying and selling not only one brand but also various brands.

The evaluation index obtained from not only the total profit / loss ratio but also the trading data (transaction data) in a narrow sense such as the trading profit / loss ratio, the unrealized profit / loss ratio, the winning rate, and the winning profit ratio can obtain the ranking data by the same procedure as the total profit / loss ratio. It is possible. By changing only the evaluation index that calculates the definition of the total profit / loss rate ranking and the issues, the trading profit / loss rate ranking, the winning rate ranking, the unrealized profit / loss rate ranking, etc. can be created by the above procedure, and they can be named by their respective names.

(Definition of revision rate ranking of earnings forecast)
For example, taking the example of Japanese stocks, we will target sales and ordinary income forecast for the current fiscal year. Based on May 2020, as an example, in May 2020, along with the announcement of the results for the fiscal year ending March 2020, the company will announce the initial forecast sales and ordinary income for the fiscal year ending March 2021. Suppose.

With this initial forecast of sales and ordinary income as 100, it is defined as a revision of the earnings forecast that the forecast figures will be revised by the time the actual figures for the fiscal year ending March 2021 announced in May 2021 are announced. do.

The revision rate of the earnings forecast is defined as the revision rate when the initial forecast sales are 100 and the upward revision is made by 30%. At the time of purchase, it becomes possible to manage whether or not there is a difference in performance between the purchase of the stock after the announcement of the correction rate of 30% and the purchase of the stock after the announcement of the correction rate of 10%.

(Previous technology)
Although there is an upward revision rate ranking, etc., the current situation is that it has not been possible to verify what kind of case has a high success probability when actually purchasing.

(Issues in ranking the revision rate of earnings forecasts)
When making upward revisions, the higher the revision rate, the more attention is paid to it, but in the end, it often becomes a high price and causes a large loss. This is evidence that the relationship between the high correction rate and the trading history and stock price has not been verified. It is a short-circuit idea that you should simply buy a stock with a high correction rate and sell a stock with a negative correction rate. Easy to produce.

(Effect of revision rate ranking of earnings forecast)
The quality of information can be further improved by adding information such as the number of revisions, the number of months ago, and the forecast for the next fiscal year, in addition to the revision rate of the earnings forecast. Not only the revision rate, but also the number of revisions, if it is the forecast value for the fiscal year ending March 2021, whether it is the revision in September 2020 6 months ago or the revision in July 8 months ago, 2022 By adding information such as how the forecast values for the fiscal year ending March 2021 will be compared to the fiscal year ending March 2021, the relationship between these information and information on stock prices and trading data will become clear.

By managing each issue in the database, it will be possible to easily rank the correction rate. By managing the initial forecast sales and ordinary income of this term, information on whether this term is the term ending March 2021 or the term ending June 2021, and the timing of the revised forecast and the figures of the revised forecast, these Numbers can be managed in the database, and rankings can be easily displayed.

At the time of purchase of a stock, the number of revisions of the stock, the number of revisions several months ago, the ranking of the revision rate, etc. are presented, which is useful for purchasing decision-making.

(Effect of revision rate ranking of earnings forecast)
If the revision rate of the earnings forecast is high, it does not mean that the success probability is high (purchasable and profitable), and if it is low, the success probability is low. There is one side that makes me.

For example, the first 10% upward revision was made as early as 10 months ago, and the fourth upward revision was 40% higher than initially expected, compared to the one-month-waiting revision. However, there is a good possibility that the probability of success is high. It is expected that such verification based on actual trading and stock prices will be possible, and by doing so, it will be possible to search for rules with a high probability of success.

(Specific example of revision rate ranking of earnings forecast)
In addition to the upward revision rate ranking, there are also comparisons with the management items, how many times, months ago, and forecasts for the next fiscal year, so these can also be ranked. Furthermore, it will lead to clarifying the relationship between the performance of stock companies and stock prices and actual trading data.

For example, an upward revision rate ranking, a profit increase rate ranking from this term forecast to the next term forecast, a revision frequency ranking, a first revision rate ranking, an early revision ranking, and the like can be considered.

For example, as for the business performance of Company F, the following two figures have been announced as of September 10, 2020.

After that, the increase was revised in February and the results were announced in May. The background is as follows.

(Actual figures for 2020.3 (actual figures for the previous term))
Sales 81,613
Operating profit 6,012
Ordinary income 4,263
Net income 1,784
Earnings per share 48.1
Dividend 26
(First revision on August 14, 2020)
2021.3 sales 85,000 (4.15%)
Operating profit 6,500 (8.1%)
Ordinary income 5,500 (29%)
Net income 1,500 (-16%)
Earnings per share dividend 24 (-7.7%)
(Announcement date: Second revision on February 10, 2021)
Sales as of 2/10 revision 89,000 (4.7% compared to the forecast) (9% compared to the previous year)
Operating income 9,000 (38% compared to forecast) (49% compared to previous year)
Ordinary income 8,000 (45% compared to the forecast) (87% compared to the previous year)
Net income 7,000 (4.67 times compared to expectations) (3.9 times)
Earnings per share 188.3 (4.67 times compared to expectations) (3.91 times)
Dividend 26
(Announcement of actual values on 21/05/14)
Sales 91,312 (up 2.5% from the forecast) (up 11% from the previous year)
Operating income 9,640 (up 7% from the previous year) (60% from the previous year)
Ordinary income 8,227 (up 2% from the forecast) (92% from the previous quarter)
Net income 8280 (up 18% from expectations) (4.6 times)
Earnings per share 222.9 (18% increase compared to expectations) (4.6 times)
Dividend 26
(New method of AI machine learning ranking process)
The AI machine learning comparison process is also performed through the following process, and the following shows which trading data (extraction conditions, classification conditions, aggregation conditions) is used to create and display the evaluation index, which is the basis of the ranking process.

The second step is the process of creating trading data to be aggregated. The third step is the creation (optional) of component trading data. The fourth step is the process of creating the profit / loss level evaluation index (the target evaluation index is calculated by the information processing system by the three methods). Up to this fourth step, the target profit and loss and the target trading data are determined. That is, the trading data set is specified by the extraction, classification, and aggregation of trading data.

In the fifth step, the evaluation index which is a component and a related element of the target profit / loss (total profit / loss, trading profit / loss, etc.) determined in the fourth step is calculated.

Up to this fifth step, the target profit and loss, the target trading data (data structure), and the evaluation index that is a variable are determined. Therefore, once the action step decides what to do, the information processing system will generate advice (evaluation, comparison, ranking, diagnosis, advice) or article generation (stock news, investor news, evaluation articles, etc.). The conditions for automation such as comparison articles, ranking news, diagnostic articles, advice articles), and the generation of articles for solving investment issues are in place. The step is to generate and display ranking articles by the information processing system based on the given trading data set, target profit / loss, and evaluation index calculated by the information processing system.

The eighth step is the generation process by the information processing system, and what is the best ranking target based on the evaluation index (single or multiple) calculated by the information processing system? It is easy to understand, and among the many ranking targets, machine learning is performed on which evaluation index is to be ranked and how, and the ranking target is determined by a ranking method that seeks the optimum solution. This can be used for article distribution, and can also be used as an article that is useful for individual investors. It can be used to solve a specific problem of an individual investor, or it can be automatically generated by the information processing system as a news article as mass media. In the former case and the latter case, what is required is different, but depending on what you want, you can change the extraction conditions and classification conditions, change the evaluation index, change the ranking target, and change the evaluation index that is the basis. , Both requests can be met.

In step 2 (display process) of the eighth step, how to rank the ranking target, which is the optimum solution, is displayed by an appropriate display method. Examples include tables, pie charts, component ranking displays, ranking displays, and the like.

(Issues in the ranking process)
There are rankings of investment products based on technical indicators, performance indicators, etc., but by ranking using the profit / loss level evaluation index obtained from the aggregated trading data, it is completely based on the ranking of investment products bought and sold by actual investors. Has a heterogeneous effect. The challenges for investors and the challenges for the media are different, so to explain this separately, it is important for investors to see their own ranking index and whether or not their ranking has risen in the ranking display. News articles are important to the media. It can be used for cooperation with stock news, or for anyone who lost stocks due to the corona disaster. Articles such as the 2020 profit amount ranking and "The top trading profit margin ranking of stocks is Softbank" can also be generated by the advice generation system and the information processing system. The reason why such articles have not appeared until now is that they did not appear in the table from the securities company that had the trading data. Although there are privacy issues, it is newsworthy enough to convey the whole picture anonymously.

(Action of ranking process)
The information generation unit 3021 calculates various profit and loss evaluation indexes based on the trading data to be aggregated, and displays the ranking results of the aggregation target and components on the display unit 23 of the terminal 2 based on the profit and loss evaluation indexes. .. Ranking results are obtained by aggregating and ranking various profit and loss level evaluation indexes for each aggregation target and component.

The process of generating and displaying the ranking article by the information processing system (see FIG. 84) and the fifth step are the same as those of the evaluation step and the comparison step. Since the evaluation index, the trading data set, the target profit / loss, etc. are determined, it is the step to decide which evaluation index is used as the basis for generating and displaying the ranking result in the information processing system. As for the target for which the ranking result is generated by the information processing system and which evaluation index is used, what is ranked first in the problem solving system and the article generation system is first, and in the advice generation system, this buying and selling The order is what is wrong with the data and how to improve it. In addition, when using it as an article generation system, the first step is how to generate ranking articles with a high number of accesses and attention by the information processing system.

(Effect of ranking process)
From the ranking results of various profit and loss level evaluation indexes of each profit and loss level, it is possible to confirm the position, the current state of the holder, the ranking of how the trading is done, and so on. For investors, the need for where and how to solve their own trading problems, whether their overall profit / loss ranking has risen or fallen today, and for the mass media, it is tied to today's news. It is expected that the information processing system will be able to generate articles that are likely to attract attention from the trading data. These effects can be expected in the system consistency of FIG. 84.

(Specific example of ranking process)
51 and 52 are diagrams showing specific examples of ranking according to the present embodiment. For example, an example is a period ranking in which stock trading data (trading data to be aggregated) is aggregated for each period (component) and arranged in descending order of total profit / loss ratio. Another example is the investor ranking, which is arranged in descending order of the winning profit margin based on the winning profit margin.

The ranking is divided into a total target ranking, a component ranking, and a multi-layered ranking, depending on what (stock, investor, etc.) is ranked. The ranking ranges from the 1st level evaluation index ranking to the 4th level evaluation index ranking depending on what (for example, the total profit / loss ratio, the winning profit ratio, etc.) is used as the standard. These ranking data are saved by the administrator and saved as a database, and can be withdrawn at any time.Since the date and time are linked to those data, time series data can be created and comparisons between last year and this year, etc. Can be easily done. It is valuable both as article data, as an individual advice history, and in terms of confirming whether the problem has been solved.

(Significance of component ranking process)
The information generation unit 3021 calculates a profit / loss level evaluation index from the aggregated trading data, and ranks the components based on the profit / loss level evaluation index. The component ranking is to calculate the profit / loss level evaluation index by the information processing system, and use the profit / loss level evaluation index obtained there to aggregate and rank the components.

(Issues in the component ranking process)
The ranking of investment products includes rankings based on technical indicators and performance indicators, but by aggregating and ranking by components using profit and loss level evaluation indicators, it is completely based on the ranking of investment products bought and sold by actual investors. Has a heterogeneous effect.

(Action of component ranking process)
The information generation unit 3021 calculates various profit and loss evaluation indexes based on the aggregated trading data, aggregates them by one component of the aggregated trading data based on those profit and loss evaluation indexes, and ranks them. The result is displayed on the display unit 23 of the terminal 2. It is the profit and loss level evaluation index of each component that constitutes the various profit and loss level evaluation indexes to be aggregated, and it is obtained by aggregating and ranking each component.

(Effect of component ranking process)
What is the position of each component in the target of aggregation based on the ranking results aggregated by the component of the target of aggregation using various profit and loss level evaluation indexes of each profit and loss level, and what is the current holder? You can check the ranking such as whether it is in a good state or how it is bought and sold.

(Specific example of component ranking process)
FIG. 52 is a diagram showing a specific example of the component ranking according to the present embodiment. For example, based on stock trading data (trading data to be aggregated), stock rankings are aggregated for each issue (component) and arranged in descending order with unrealized losses, or are arranged in descending order of profits that are most profitable in short-term trading. The stock ranking is an example. (These are rather articles for the media.) An example is the stock (component) ranking arranged in descending order of unrealized profit ratio based on the unrealized profit ratio in Mr. A's trading data (aggregated trading data). be. (These are articles (contents) for personal advice.) Another example is to use stock A as a component and make a winning profit margin ranking with investors as components. For the media, it is the trading data (extraction condition: stock) of the stocks that had news, by investment target, ranking by investor if the component is an investor, and people who have bought and sold on Twitter by medium. It is possible to put out a ranking of the number of times the stock has been bought and sold, and it is also possible to rank the stocks bought and sold by those who had high results this month. The reason why these articles can be generated by the information processing system is system consistency.

(Significance of the multi-layered ranking process)
The information generation unit 3021 calculates a profit / loss level evaluation index based on the aggregated trading data, and ranks each component B with a certain component A as an axis based on the profit / loss level evaluation index. Since two or more components are used, it is expressed as a multi-layer type.

(Issues in the multi-layered ranking process)
The ranking of investment products includes technical indicators, rankings based on performance indicators, and the above-mentioned ranking process. Using the profit / loss level evaluation indicators obtained from trading data, each component B is centered on a certain component A. By ranking, it has a completely different effect.

(Action of multi-layered ranking process)
The information generation unit 3021 calculates various profit / loss level evaluation indexes based on the trading data to be aggregated, and based on those profit / loss level evaluation indexes, terminals the ranking result for each component B with the component A as the axis. It is displayed on the display unit 23 of 2. The ranking result is obtained by ranking each component B with the component A as the axis.

(Effect of multi-layered ranking process)
By using various profit and loss level evaluation indexes of each profit and loss level and showing the ranking result for each component with a certain component as the axis, the component A in the total target is used as the axis. If so, it is possible to confirm the position of the component B, the current state of the holder, the order of buying and selling, and the like.

For the media, the winning rate ranking of investors who have bought and sold on Twitter if the component A is an investor and B is a medium in the trading data (extraction condition: stock) of the stocks that had news by investment target. It is also possible to issue such as, and this month (aggregation target trading data by period: extraction condition = this month), component A is an investor, component B is a brand, and profit / loss is a trading profit / loss ratio (extraction condition: trading profit / loss ratio> 20). %), It is also possible to rank the stocks bought and sold by those who have achieved high results. The reason why these articles can be generated by the information processing system lies in the consistency of the advice generation system.

(Specific example of multi-layered ranking process)
For example, FIG. 53 is a diagram showing a specific example of multi-layered ranking. When the unrealized profit / loss ratio is aggregated and the investors and stocks are used as components for ranking, Mr. A, who has the most unrealized loss, is identified, and it becomes clear which stock has the unrealized loss.

If the total profit / loss ratio is aggregated and the investor and the fiscal year are the components, the investor ranking of the total profit / loss ratio in 2019, the total profit / loss ratio ranking in 2018, etc. will be clarified. If it is a brand, the brand ranking can be displayed.

FIG. 53 also exemplifies a ranking example in which Mr. A is the target of aggregation and the brand and the year are the components.

For example, based on the trading data to be aggregated, which is stocks, it is aggregated for each issue (component B) centering on Mr. A (component A), and the ranking by issue that Mr. A has an unrealized loss, profit in short-term trading. An example is the stock rankings that often appear. By clarifying the position of the components in Mr. A's profit and loss, there is an effect that it has a great influence on how to buy and sell the components to be aggregated.

Clarifying the position of a component in the profit and loss to be aggregated has the effect of greatly affecting how to buy and sell the component to be aggregated. Although the case where there are two components is illustrated, the same applies to three or more components.

(Issues in ranking for each aggregation target)
The information generation unit 3021 relates to the ranking of the trading status or the holding status within the standard by ranking within the standard (for example, for each investment target) using the trading profit / loss level evaluation index or the unrealized profit / loss level evaluation index. Generate information.

Ranking for each aggregation target enables more detailed analysis. The multi-layered ranking display that aggregates the components around the components can be further enhanced. While the multi-layered ranking is derived from one aggregated trading data, the ranking for each aggregated object is derived from a plurality of aggregated trading data. By ranking using a plurality of aggregated trading data aggregated from various viewpoints, more multifaceted ranking becomes possible.

(Definition of ranking for each aggregation target)
Using the components in the aggregated trading data as the axis is the same as the multi-layered ranking, but the rankings created by re-aggregating the aggregated trading data with the components as the axis are aggregated. It is defined as ranking for each target.

(Effect of ranking for each aggregation target)
There is an effect that it is possible to know more deeply by ranking the aggregation target to be known by the profit / loss level evaluation index with a certain component as the axis.

(Specific example of ranking for each aggregation target)
FIG. 54 is a diagram showing a specific example for each ranking for each aggregation target according to the present embodiment. The profit / loss level evaluation index is calculated by the information processing system, and the profit / loss level evaluation index is aggregated and ranked for each aggregation target. By ranking in the order of the trading profit rate from the aggregated trading data of Mr. A, Mr. B, and Mr. C, it is possible to obtain the result that the trading profit rate is higher in the order of Mr. C, Mr. B, and Mr. A. By aggregating for each issue (aggregation target), it is possible to display the issue ranking for the profit / loss level evaluation index (for example, the unrealized loss rate). There is also a multi-layered aggregation target ranking that makes it clear at a glance which issues have a large unrealized loss rate. These are rather media articles.

By using the investor as the axis of the component and using the profit / loss level evaluation index as the unrealized profit ratio, it is possible to display the ranking in which the unrealized profit ratio of the investor is arranged in the order of stocks. For example, if the trading data of Mr. A's investment products is aggregated, there are both Mr. B and Mr. C, and virtual currency, FX, stocks, etc. are the axes of the components, and it is the most profitable stock in a cross-cutting manner. You can see who the investor is.

On the contrary, when the issue is the axis, the issue A of Mr. A's virtual currency and the issue C of the stocks bought and sold by Mr. C are lined up in the same ranking, and Mr. A's issue ranking by investors with high winning profit margins. One example is the result that the profit margin of the virtual currency brand A is the highest. Investors, investment types, investment groups, etc. are also components. When stocks are included in the total, investors, stocks, dates, etc. can also be the axes. These can be aimed at individual investors, as well as media and manager information, investment information news, and so on.

FIG. 55 is a diagram showing a specific example for each ranking for each aggregation target according to the present embodiment. For example, by dividing the aggregation target of the excellent stock group and the aggregation target of the high dividend group into the components of the date range in the winning profit margin ranking, it is possible to rank the high dividend group as the highest in 2018. .. For example, in the winning profit margin ranking for each investor around the period of 2019, the stock A of investor A's virtual currency is the top, and the stock A of investor B's stock is second. Ranking is also possible. It can also be used for fact-finding surveys and behavioral surveys of Japanese investors.

By deciding the axis of the aggregation target and the aggregation target to be ranked, there is an effect that it becomes possible to confirm the state of the aggregation target in a more multifaceted and multi-layered manner. Ranking a plurality of aggregated trading data for each aggregated object with each profit / loss level evaluation index as an axis is defined as an aggregated object type ranking.

So far, the ranking process, the multi-layered ranking process, and the aggregation target type ranking process have been explained. Ranking is what is ranked (ranked) by what criteria. The standard is a profit / loss level evaluation index, and the component ranking process and the multi-layered ranking process (multiple components) are used when ranking the components, and the aggregation target ranking process is used when ranking the aggregation targets. .. These are structural differences, but the next level ranking divides the profit and loss level evaluation index into levels.

(Meaning of level ranking)
The ranking by level refers to displaying the ranking based on the trading data to be aggregated, calculating the profit / loss level evaluation index for each profit / loss, and ranking based on those profit / loss level evaluation indexes. Level rankings can be used for multi-layered rankings, and level rankings can be applied to aggregated rankings as well. This is because both the multi-layered ranking and the aggregated ranking have a calculation process of the profit / loss level evaluation index, and the calculation process is calculated by the information processing system of the profit / loss level evaluation index for each profit / loss level. Process is carried out.

Hereinafter, the normal level ranking will be described except when there is a special effect.

(Issues in level ranking)
For example, in the trading profit / loss ratio ranking for each component to be aggregated, the ranking such as the holding status such as the unrealized profit rate of the component is not taken into consideration. By calculating the profit and loss level evaluation index according to the profit and loss level from the overall profit and loss situation to the detailed profit and loss situation by the information processing system and performing the ranking, multi-faceted and multi-step ranking becomes possible.

(Necessity of level ranking)
FIG. 56 is a diagram showing a profit / loss level ranking according to the present embodiment. The profit and loss level is divided into four stages depending on how it is divided and how it is perceived.

For example, it is the profit / loss of the total profit / loss level (1st level) that comprehensively shows the results of the investment of the A brand, and the profit / loss of the winning profit level (3rd level) that only the winning trades are extracted from the traded. ).

In the case of the total profit / loss level, the total profit / loss ratio ranking is, for example, a shallow overall ranking in which the S issue is ranked 3rd and the B issue is ranked 2nd. In this case, it is only vaguely known which is the brand that produced the result.

As for the winning rate of the 2nd level, it is gradually found that the winning rate is not high, such as 6th place for S brand and 5th place for B brand, and when ranked by the winning profit margin of 3rd level, S brand is winning profit. It can be seen that the profit margin is high when the rate ranking is 1st and the B issue is 2nd, and the unrealized loss rate is 1st for the S issue and 2nd for the B issue. It will be possible to deeply understand the target of aggregation, such as finding out that it is a stock that will have an unrealized loss if it continues. These will be detailed information, but they will be very useful and valuable information for investors, large investors, hedge funds, etc.

In light of investors, for example, the total profit and loss of Mr. A's investment is the profit and loss of the total profit and loss level, and the profit and loss of the winning profit level is the extraction of only the winning trades among the traded and traded. ..

In the case of the total profit / loss level, the total profit / loss ratio ranking is, for example, a shallow overall ranking of Mr. A in 3rd place and Mr. B in 10th place. On the other hand, when ranking by the third level of winning profit margin, Mr. A is ranked 5th in the winning profit margin ranking, Mr. B is ranked 1st, and the winning percentage is 1st in Mr. A and 10th in B. Can be understood. These will also become detailed information, but for investors, large investors, hedge funds, etc., they will be extremely useful and valuable information for achieving investment results.

On the other hand, for M stocks, the deeper the profit and loss ranking, such as the unrealized loss ratio of 3rd place and the winning profit margin of 100th place, the finer the ranking becomes possible, and how is it winning? You will be able to understand what is weak. Such information is suitable for stock magazines, stock newspapers, stock blogs, and the like.

The same applies to the ranking display of all aggregate targets such as stock ranking, investor ranking, investment type ranking, product ranking, and stock A and excellent stock group A ranking display. These may be one of the necessary information for a little larger media. Of course, the same applies to component rankings, multi-layered rankings, and aggregated rankings.

(Action of level ranking)
Follow the procedure below to perform level ranking. That is, the information generation unit 3021 performs comprehensive ranking display by calculating the profit / loss level evaluation index of total profit / loss, ranking display by the profit / loss level evaluation index of the second level unrealized profit / loss and the trading profit / loss level, and the third level win. And ranking display such as winning profit margin at the level divided into losses, ranking display with market price after selling at the 4th level and benchmark evaluation value considering the bench mark increase / decrease rate, and detailed ranking display Is possible for each level.

Even for one brand, there are various trading methods and they are practiced. This diverse collection of trading data cannot be accurately ranked unless it is multifaceted and multi-stepped based on the results of various profits and losses. These are used not only for ordinary rankings, but also for component rankings, multi-layered rankings, aggregated rankings, and the like.

(Effect of level ranking)
By displaying the multi-faceted and multi-step ranking of the trading data to be aggregated, there is an effect that the holding status and trading status of the aggregation target can be accurately grasped. By level comparison, many profit and loss level evaluation indexes at each level are calculated by the information processing system, so it is possible to display more detailed and deep rankings in a wide range. Similarly, ranking by level-based profit and loss evaluation index will have more effect.

(Definition of 1st level ranking)
The first level ranking is a ranking using the total profit / loss level evaluation index used in the total profit / loss level.

(Issues for the 1st level ranking)
The ranking of the target of aggregation (for example, stocks) is generally based on technical indicators, performance indicators, etc., but it goes on without knowing what kind of result was actually bought and sold. There are many investors who lose money even though the stock price is rising, and the investors who actually bought and sold the stocks that prevailed in the world have not come out to the world at all, such as whether they made a profit or lost.

(Means of 1st level ranking)
The information generation unit 3021 calculates various comprehensive profit / loss level evaluation indexes in order to evaluate the total profit / loss of the aggregated trading data, and uses those comprehensive profit / loss level evaluation indexes to determine the total profit / loss level evaluation index of the aggregated target. Ranking.

(Effect of 1st level ranking)
By ranking and displaying the aggregated object or component using various total profit and loss level evaluation indicators of total profit and loss, how the aggregated object or component is handled in the market, and the total loss for the past year You can see the ranking such as whether you are making a profit, whether you are making a profit, and how much the profit is.

By ranking and displaying the aggregated object or component with these total profit / loss level evaluation indicators, the characteristics of buying and selling of the aggregated object or component become clear, and the various comprehensive profit / loss level evaluation indicators of the aggregated object or component become clear. The ranking result of is clarified. It is possible to confirm what kind of trading is being carried out on the aggregation target or component, and the order of the aggregation target or component.

(Specific example of 1st level ranking)
For example, stock A has a total profit / loss of 1.5 times and is ranked third. On the other hand, the B stock can be expressed as having a total profit / loss of 0.85 times and a ranking of 10th. For example, in 2019, it is possible to display Mr. A's total profit / loss ratio of 30% and ranking 10th, and Mr. B's total profit / loss ratio of 10% and 120th.

By ranking (ranking) these comprehensive profit / loss level evaluation indexes for each aggregation target or component, the characteristics of buying and selling of the aggregation target or component become clear, and various synthesis of the aggregation target or component. The ranking in the profit and loss level evaluation index becomes clear. It is possible to determine what kind of trading character the aggregation target or component has. By ranking by the total profit / loss level, it is possible to rank what kind of total profit / loss is brought about by the buying and selling of the aggregated object or component.

Since the total profit / loss includes both the trading data held and the trading data, the total profit / loss status of the aggregation target or the component is grasped, and the total profit / loss level evaluation index is calculated by the information processing system and ranked. Therefore, the overall picture of the buying and selling of the aggregated object or component can be understood.

(Issues for the second level ranking)
Since the ranking for the total profit and loss of the investment products includes the fixed profit and the undetermined profit that were bought and sold, only the total ranking can be displayed. The ranking display result obtained from the trading profit / loss level evaluation index for trading profit / loss shows what kind of trading was done and what kind of result was obtained, such as the winning rate, trading profit / loss ratio, trading period, etc. that could not be understood from the total profit / loss. Can be displayed by ranking.

(Means of 2nd level ranking)
The information generation unit 3021 calculates various trading profit / loss level evaluation indexes in order to evaluate the trading profit / loss of the trading data to be aggregated, and uses those trading profit / loss level evaluation indexes to determine the trading status of the aggregated target or component. Display ranking.

(Effect of 2nd level ranking)
By ranking and displaying the aggregated object or component using various trading profit / loss level evaluation indicators of trading profit / loss, unrealized profit / loss level evaluation index of unrealized profit / loss, etc., how the aggregated object or component is handled in the market. Or, you can see the trading status by comparing with others in the average trading profit / loss ratio ranking, holding period ranking, winning rate ranking, unrealized profit / loss ratio ranking, etc.

By ranking and displaying the aggregated object or component in these trading profit / loss (or unrealized profit / loss) level evaluation indicators, the characteristics of trading and holding of the aggregated object or component are highlighted, and the characteristics of the aggregated object or component are highlighted. The ranking display result in various trading profit / loss (or unrealized profit / loss) level evaluation indexes is clarified. It is possible to determine what kind of trading character or holding status the aggregation target or component has.

(Specific example of the second level ranking)
The S stocks have the highest trading profit / loss ratio, the winning rate of 60%, the 6th place, and the unrealized profit / loss ratio of 5th place. On the other hand, for issue B, the trading profit / loss (or unrealized profit / loss) level evaluation index for each aggregate target or component, such as the trading profit / loss ratio of 2nd place, the winning rate of 5th place, and the unrealized profit / loss ratio of 250th place, is trading. It is done at the profit / loss (or unrealized profit / loss) level. In order to display the ranking from the trading data, it is possible to grasp the trading status of the relevant aggregation target or component, and it is possible to rank and display whether it is a stock with a strong short-term trading orientation or a stock with a long holding period in the medium to long term. become.

(Issues of trading profit / loss level evaluation index ranking)
Since the ranking for the total profit and loss of the investment products includes the fixed profit and the undetermined profit that were bought and sold, only the total ranking can be displayed. The ranking display result obtained from the trading profit / loss level evaluation index for trading profit / loss shows what kind of trading was done and what kind of result was obtained, such as winning percentage, trading profit / loss ratio, trading period, etc. that could not be understood from the total profit / loss. Can be displayed in the ranking.

(Means for ranking the trading profit / loss level evaluation index)
The information generation unit 3021 calculates various trading profit / loss level evaluation indexes in order to evaluate the trading profit / loss of the trading data to be aggregated, and uses the trading profit / loss level evaluation indexes to evaluate the trading status of the aggregation target or the component. Is displayed in the ranking.

(Effect of trading profit / loss level evaluation index ranking)
By displaying the aggregated object or component in a ranking using various trading profit / loss level evaluation indicators, etc., how the aggregated object or component is handled in the market, the average trading profit / loss ratio ranking, holding You can see the trading status by comparing with others about the period ranking, winning percentage ranking, etc.

By ranking and displaying the aggregation target or component with these trading profit / loss level evaluation indexes, the characteristics of trading of the aggregation target or component become clear, and various trading profit / loss level evaluation indicators of the aggregation target or component can be used. The ranking display result of is clarified. It is possible to determine what kind of trading character the aggregation target or component has.

(Specific example of trading profit / loss level evaluation index ranking)
Stock A has a trading profit / loss ratio of 100th, but a winning percentage of 80%, which is the best result. On the other hand, the B issue has the second highest trading profit / loss ratio and the fifth highest winning percentage. The ranking display for each trading profit / loss level evaluation index for each aggregation target or component is performed at the trading profit / loss level. For the media, for example, which stock was ranked first in October, which stock was ranked first in November, etc., can be generated by the information processing system on a regular basis and updated as needed. , Accepted as valuable information for investors. In order to display the ranking from the data that has already been bought and sold, it is possible to grasp the trading status of the relevant aggregation target or component, and it is possible to rank and display whether it is a stock with a strong short-term trading orientation or a stock with a long holding period in the medium to long term. It will be possible.

(Issues in ranking the unrealized profit / loss level evaluation index)
When targeting unrealized profits and losses, the holding status and trading status cannot be known in detail because both the holding status and the trading status are mixed at the total profit and loss level. By evaluating the unrealized profit / loss level, the unrealized profit / loss ratio, the average holding period, the average bid price, the average profit amount, etc. can be known.

(Means for ranking unrealized profit / loss level evaluation indicators)
The information generation unit 3021 calculates various unrealized profit / loss level evaluation indexes in order to evaluate the unrealized profit / loss of the unreversed trading data aggregated for each aggregation target, and uses those unrealized profit / loss level evaluation indexes to make the aggregation. The possession status of the target or component is displayed in the ranking.

(Effect of unrealized profit / loss level evaluation index ranking)
By displaying the holding status of the aggregated object or component in a ranking using various unrealized gains / losses level evaluation indicators, the holding status of the owner of the aggregated object or component, etc. I understand.

(Specific example of unrealized profit / loss level evaluation index ranking)
For example, the following ranking display is possible.

A-shares have the highest percentage of people with unrealized gains, and the average unrealized gain ratio is 50% (1.5 times), which is the highest. On the other hand, in the B share, the person who has an unrealized loss is ranked 100th, and the average unrealized loss rate is 0.92 times that of the 2nd place.

In addition, Mr. A has a low unrealized profit / loss ratio and is in the 300th place, and can display that he has too much unrealized loss compared to others. For the media, for example, which stock has the highest unrealized gain rate in October and which stock has the highest unrealized loss rate in November can be generated by the information processing system on a regular basis and is updated as needed. Therefore, it is accepted as valuable information for investors. This can be expected to have the effect of revealing the overall picture and situation of the stocks held by the grain difference.

At this unrealized profit / loss level, the status of holding the aggregated object or component can be ranked and displayed. It has the effect of being able to grasp the status such as how much the possession status of the aggregation target or component is as a whole.

(Issues of the 3rd level evaluation index ranking)
Since the ranking for the second level of investment products includes winning profit and losing loss, only the total trading profit / loss and unrealized profit / loss ranking can be displayed.

As a ranking display result obtained from the winning profit level evaluation index for the winning profit, how did you win, such as the winning profit, the winning profit margin, the winning trading value, and the winning trading period, which were not known from the trading profit / loss? Can be displayed in the ranking.

(Means for ranking the winning profit level evaluation index)
The information generation unit 3021 calculates various winning profit level evaluation indexes in order to evaluate the winning profit of the aggregated trading data, and uses the winning profit level evaluation indexes to obtain the trading status of the aggregated target or the component. Is displayed in the ranking.

(Effect of winning profit level evaluation index ranking)
By displaying the aggregated object or component in the ranking using various winning profit level evaluation indexes, how the aggregated object or component is handled in the market, the average winning rate of return ranking or the annual winning profit. You can see the trading status by comparing with others such as rate ranking, winning profit ranking, etc.

By ranking and displaying the aggregation target or component with these winning profit level evaluation indexes, the characteristics of buying and selling of the aggregation target or component become clear, and the various winning profit level evaluation indexes of the aggregation target or component can be used. The ranking display result becomes clear. It is possible to determine how the aggregation target or component has won.

(Specific example of winning profit level evaluation index ranking)
The A issue has a winning profit margin of 100th place, while the B issue has a ranking display for each aggregation target or component such as the winning profit margin of 2nd place, and for each winning profit level evaluation index, at the winning profit level. .. In order to display the ranking from the data that has been bought and sold and the winning profit is recorded, it is possible to grasp how to win the aggregation target or the component, and it is possible to display the ranking of the stock that is easy to win or the stock that is difficult to win. For the media, for example, what stocks many investors won in 2020, what stocks lost significantly, etc. can be generated by the information processing system on a regular basis and are updated as needed. Therefore, it attracts attention as an article with news characteristics. Investors can also see at a glance which stocks are easy to win and which stocks are easy to lose, so they are accepted as valuable information.

(Specific example of 3rd level ranking)
An example of evaluating a winning trade and a losing trade, that is, a winning profit and a losing loss from the traded data will be described. For example, regarding the winning trade, the winning profit margin of the A stock is 30th, while the winning profit margin of the B share is the 2nd place. On the other hand, regarding losing trades, A-shares have an average bid price of 4800 yen and an average selling price of 4500 yen, and have an average holding period of 5 days, forcing a loss cut. On the other hand, the losing trade of B shares is an average buy at 165 yen and an average sale at 157 yen, and the average holding period is 7 days, which is a loss cut. As a result of calculating the winning profit (or losing loss) level evaluation index by dividing the traded data into winning trades and losing trades, comparison between each aggregation target of winning trades, comparison between each component, and aggregation of losing trades. Comparison between objects (or components) becomes possible, and information for each aggregation object (or component) that is very meaningful for the trader can be obtained.

The information generation unit 3021 calculates the unrealized gain (or loss) level evaluation index separately for the unrealized loss and the unrealized gain, and compares the unrealized gain (or loss) level evaluation index. For example, A-shares with unrealized gains account for 80% of the holders, with an average rate of return of 70% and an average holding period of one year. On the other hand, only 20% of the holders have unrealized gains on B shares, with an average purchase price of 150 yen, a rate of return of 10%, and a holding period of one year. 20% of A-share holders still have unrealized losses, the average bid price is 5,500 yen, the unrealized loss rate is -10%, and the holding period is half a year.

For example, the winning trade of stock A has an average buy unit price of 4000 yen and a sell price of 4500 yen, the average rate of return is 12%, and the ranking is 10th, and the average holding period of 2 weeks is 100th. can.

On the other hand, regarding losing trades, stock A has an average buy price of 4800 yen and an average selling price of 4500 yen. It is used such as ranking 50th.

The information generation unit 3021 divides the traded data into winning trades and losing trades, calculates each winning profit (or losing loss) level evaluation index, and uses the winning profit (or losing loss) level evaluation index. And rank. It is possible to rank the profit rate of each stock of winning trades, the loss rate ranking of losing trades, etc., and it is possible to easily extract stocks with a short average trading period ranking and a high average trading profit ratio. For those who trade, it will be possible to obtain very meaningful information for each stock and stocks with a strong winning profit level evaluation index.

The information generation unit 3021 calculates the unrealized gain (or unrealized loss) level evaluation index separately for the unrealized loss and the unrealized gain, and ranks the unrealized gain (or unrealized loss) level evaluation index.

For example, among the holders of stock A, 80% of the holders record unrealized gains, which is the third in the unrealized gain weight ranking, and the average unrealized gain ratio is 70%, which is the first in the unrealized gain ranking. .. On the other hand, only 20% of the holders have unrealized gains on stock B, which is 250th in the unrealized gain weight ranking, 10% in the unrealized gain ratio, and 150th in the unrealized gain ratio ranking.

On the other hand, regarding unrealized losses, the ratio of those who have unrealized losses among the A stock holders is 20% of the holders, the ranking is the first (the smaller the ranking, the higher the ranking), and the unrealized loss rate is suppressed to -8%. The ranking of the unrealized loss rate is 25th. On the other hand, those who still have unrealized losses on stock B account for 80% of the holders, 250th in the unrealized loss weight ranking, but the unrealized loss rate is 3%, and the unrealized loss rate ranking is 7th (the smaller the ranking, the higher the ranking). ).

How many people have unrealized gains, who can grasp the purchase status and unrealized profit / loss status of the stocks they own, what is the ranking, whether the unrealized profit ratio is high or low compared to others, and what is the higher stock? It has the effect of making it possible to obtain information that has not been known to the world, such as. In other words, it is possible to grasp the purchase status and unrealized profit / loss status of the holding aggregation target (or component), how many people have unrealized profits, how much they are buying, how is it compared to others, etc. It has the effect of making it possible to obtain information that was unknown to the world.

(Specific example of 4th level ranking)
The information generation unit 3021 ranks using the winning pattern analysis and the losing pattern analysis, which have different characteristics even in the same winning trade, at the fourth level of profit and loss. For example, for A-shares, buying and selling of winning pattern 1 (buying price <selling price <current price) occupies 80%, winning pattern 1 weight is 1st, the remaining 10% is pattern 2, and weight ranking is 250th and 10%. It is pattern 3 and the weight ranking is 260th. Since pattern 1 is "buy price <sell price <current price", it can be said that if the weight of the winning pattern of pattern 1 is high, stable short-term trading is easy to be performed.

In particular, it can be said that the target of aggregation, which has a high winning profit margin in winning pattern 1, is a short-term trading flower-shaped issue.

On the other hand, in the pattern analysis of B shares, the losing pattern occupies most, the pattern of "buying price> selling price> current price" which is the losing pattern 3 occupies 80% of the losing pattern, and the losing pattern 3 weight ranking is the first place and loses. It can be expressed as a stock with a large number of people who are trading.

I sold it with a loss cut immediately after I bought it, but the loss rate is suppressed to minus 2%, and in the trading loss rate ranking in the losing pattern 3, I frequently lose cut at the 5th place (smaller one is higher). , Loss is a subject of aggregation that is suppressed.

(Ranking using unrealized gain pattern level evaluation index)
On the other hand, whether the unrealized gain is higher than the benchmark or lower than the benchmark has a big difference in meaning even if the unrealized gain is the same. Stocks that are well above the benchmark and form unrealized gains are highly rated, and conversely, those that are well below the benchmark and are forming unrealized losses are rated low.

For example, A-shares have unrealized gains with returns well above the Nikkei 225, with a benchmark overrun rate of 50%, a benchmark overrun rate ranking of 3rd, and A-share holdings and purchases above the Nikkei 225. ..

On the other hand, in the pattern analysis of unrealized gains and losses of B shares, there is an unrealized loss, a loss below the Nikkei average is recorded, the benchmark lowering rate is 1%, the rate of decline is almost the same as the Nikkei average, and even if it is held, there is little taste. It can be said that it is a target.

What kind of aggregation target (or component) is the aggregation target (or component) that exceeds the benchmark but is much higher than the benchmark, and should the aggregation target (or component) that is significantly below the benchmark be reviewed? It has the effect of being a judgment factor. An example of ranking display using win pattern analysis and lose pattern analysis at the profit / loss level is shown.

For example, in the A stock, 80% of the trading is for winning pattern 1 (buying price <selling price <current price), the remaining 10% is pattern 2, and 10% is pattern 3. In pattern 1, even after selling at "buy price <sell price <current price", the stock price is stable and it is possible to buy and sell with a margin. It can be said that it is an aggregation target (or component) suitable for short-term trading. On the other hand, in the pattern analysis of the B share, the losing pattern occupies most, and the pattern of "buying price> selling price> current price" which is the losing pattern 3 occupies 80% of the losing pattern. It was sold at a loss cut immediately after it was bought, but it is currently in a state of lowering than that, and most of the patterns were better to sell than to keep holding it.

By using the winning pattern analysis and the losing pattern analysis in this way, it is possible to win with a margin even in the same winning trade, or finally win with the aggregation target (or component) that will lose profit unless sold immediately. You can see the situation.

In pattern 2, cases such as "buy price <current price <sell price" and "current price <buy price <sell price" are superior in terms of trading skill, but the selection target (or component) may be bad. It can bring great effects such as no.

(Ranking using unrealized gain pattern level evaluation index)
On the other hand, whether the unrealized gain is the rate of increase or lower of the aggregated object (or component) held above the benchmark has a big difference in meaning even if the unrealized gain is the same.

For example, A-shares have unrealized gains with returns well above the Nikkei 225, and holding and purchasing A-shares has resulted in above the Nikkei 225.

On the other hand, in the pattern analysis of unrealized gains and losses of B shares, there is an unrealized loss, and a loss far below the Nikkei average is recorded. At the moment, the choice is wrong, but there is a dividend, so it is necessary to consider that amount as well.

Even if they have the same unrealized gain and the same unrealized loss, if they exceed the benchmark, it can be said that the selection of the aggregation target (or component) was correct. If it is below the benchmark, it will have the effect of making a strategy that it is necessary to review the aggregation target (or component) that is in possession.

The information generation unit 3021 calculates the winning pattern level evaluation index and ranks the stocks by the winning pattern level evaluation index. For example, the A stock is used such that the trading profit margin ranking is 3rd and the B stock is 100th.

The profit / loss level is divided into each stage, and the stock is ranked based on various profit / loss evaluation indexes of the trading data at the target profit / loss level.

Specific examples of rankings at each level are as follows.

(Ranking using the 1st level comprehensive profit / loss level evaluation index for each issue)
In order to compare from the trading data, it is possible to grasp the trading status of the stock, and it is possible to rank whether it is a stock with a strong short-term trading orientation or a stock with a long holding period in the medium to long term, and short-term trading. It will be possible to know the stocks that are suitable for trading and the stocks that are suitable for medium- to long-term holding in the ranking status.

For unrealized gains and losses, for example, the following rankings are possible. Stock A has an average unrealized gain ratio of 50% (1.5 times), a ranking of 7th, a holding period of 1 year or more and a holding period ranking of 10th among the holdings, and has an unrealized loss. People use it as 7th in the ranking with only 20%, average 5% in loss, and 150th in the unrealized loss rate ranking.

On the other hand, for B stocks, 70% of the people have unrealized losses, ranking 250th, and the average unrealized loss rate is 5%, but the ranking is 200th, the holding period is half a year on average, and the holding period ranking is 150. It is ranked, and 80% of the people who purchased it and have unrealized losses account for it, and it is used for ranking 300th. For the media, B stock is famous and has a high dividend, but in reality, so many people are losing money by holding it, or conversely, A stock is not paying dividends and is attracting attention. It is also possible to provide information that there are no stocks, but those who are actually investing have very large unrealized gains. It can generate a lot of information that is meaningful to investors.

(Ranking using the 2nd level trading profit / loss level evaluation index for each issue)
At this unrealized gain / loss level, it is possible to rank the holding status of the stock. There is an effect that it is possible to grasp the situation such as which stock has a large unrealized gain ratio while the holding status is positive and which stock has a large unrealized loss ratio.

(Ranking using the 3rd level winning profit level evaluation index for each issue)
In the third level ranking, the information generation unit 3021 calculates the winning profit level evaluation index at the level of evaluating the winning trade and the losing trade, that is, the winning profit and the losing loss separately from the traded data, and they are used. Ranking the winning profit level evaluation index for each issue. In both the following multi-layered level ranking process and aggregation target level ranking, the profit and loss evaluation index is calculated by the information processing system in this level ranking process.

(Meaning of component ranking)
When the target of aggregation is stocks, the stocks and investors are the components (components to be aggregated). The winning profit margin of each stock constitutes the winning profit margin of the stock, and by ranking it for each stock, the component ranking can be obtained. Aggregating by component includes aggregation by stock A, aggregation by a certain period, aggregation by an investor group, aggregation by a stock group, and the like. When the target of aggregation is an investor, brands and products become components. Then, the products A, B, and the like are totaled. When the target of aggregation is a product, the components are stocks, FX, virtual currency, investment trusts, etc., and it is possible to know which product has the highest trading profit / loss ratio.

For example, among the stocks that are the constituents of stocks, what is the ranking of the trading profit margin of stock A, what is the stock with the higher trading profit margin, and what is the unrealized profit margin ranking? You will be able to understand the position of the holding status and trading status of the stock. For example, in the winning profit margin ranking of the excellent stock group, which is the target of aggregation, the characteristics of the A stock become clearer in the ranking ranking of the A stock. For example, looking at the winning profit rate ranking ranking, losing loss rate ranking ranking, etc. of Investor A and Investor B included in the aggregated trading data has the effect of clarifying the difference between trading and holding of both. .. For example, it is possible to compare the winning profit margin ranking ranking of a product called virtual currency by brand and the winning profit margin ranking ranking of an investment product called stock.

By confirming the ranking of each profit and loss evaluation index to be aggregated, there is an effect that it becomes possible to confirm the state of the aggregated object in a more multifaceted and multi-layered manner. For example, stock A has a high trading profit margin among stocks, is ranked 10th, has a high unrealized profit margin, is ranked 20th, and has a high short-term trading profit margin of 15th. Providing the ranking result is an example.

The result of the stock of component A, which is the subject of aggregation as an investor, has a higher trading profit margin than the average, is ranked 20th, has a high unrealized profit margin, and is ranked 30th, and profits are rising. In particular, stocks with a long holding period have swelling unrealized profits, and the rate of return on short-term trading is 5th, which is considerably higher than the average.

As described above, the ranking is performed for each investor's profit and loss evaluation index. For example, by ranking the unrealized loss rate, trading frequency, trading profit rate, etc. for each investor, it becomes possible to better understand the trading status, holding status, investor status, etc. of Investor A.

(What are the components to be aggregated and the components to be the axis)
When the target of aggregation is stocks, the stocks and investors are the components (components to be aggregated). Among them, if the issue is the axis, the ranking for each investor is required, and conversely, if the investor is the axis, the ranking for each issue is required. Although it is assumed that two components are used, three or more components may be used.

The winning profit margin of each stock constitutes the winning profit margin of each stock, and the winning profit margin of each stock is further subdivided into the winning profit margin of each investor, which is ranked by investor. By attaching, ranking can be obtained. You can create rankings in multiple layers. When the target of aggregation is an investor, stocks, products, etc. become components, and it is possible to determine which is the axis and which is ranked.

When the target of aggregation is a product, the components are stocks, FX, virtual transit, investment trusts, etc., and it is possible to know which stock has the highest trading profit / loss ratio centered on the virtual currency.

(What are the components)
A component is defined as an element included in the trading data to be aggregated. For example, when the trading data of Mr. A's investment product is aggregated, virtual currency, FX, stocks, etc. become the axis of the component, and the brand becomes the component among them. On the contrary, when the issue is the axis, the issue A of the virtual currency and the issue B of the stock are lined up in the same ranking, and the result is that the issue A of the virtual currency is the best as the issue ranking with the highest winning profit margin. It is also an example that it can be obtained. Investors, investment types, investment groups, etc. are also components.

When stocks are included in the total, investors, stocks, dates, etc. can also be the axes. For example, among the stocks that are the constituents of stocks, what is the ranking of the trading profit margin of stock A, and the rankings of Mr. A and Mr. B that make up the trading profit margin of stock A are multi-layered. By displaying it, it is possible to rank the person who is the most profitable in this brand to indicate that it is Mr. A.

For example, it is possible to rank that A stock is the highest in the winning profit margin ranking of the excellent stock group, but it was the highest in 2018 when divided by the component of the date range.

For example, if the winning profit margin of investor A included in the aggregated trading data is divided by product, the stock is the highest and the second is the investment trust and the like can be ranked.

For example, with the period of 2019 as the axis, the stock A of the virtual currency is the top in the winning profit margin ranking for each stock, and the stock A of the stock can be ranked second.

By deciding the axis of the aggregation target and the component to be ranked, there is an effect that it becomes possible to confirm the state of the aggregation target in a more multifaceted and multi-layered manner. For example, in the aggregation target of stocks, A-shares have a high trading profit margin and are ranked 10th, and among them, Mr. A occupies the 1st place.

In the aggregate target of investors, the results of the stock of component A have a higher trading profit margin than the average, and the ranking is 20th, and among them, the trading profit margin of stock A contributes the most. Will be possible. For example, by ranking the unrealized loss rate, trading frequency, trading profit rate, etc. for each issue centered on the investor, it is possible to better understand the investor's situation such as the trading status and holding status of investor A. Become.

(Issues in the AI ranking process)
In the above-mentioned ranking process, there is a problem that there are many options for deciding which ranking target is used, which profit / loss is ranked, and which evaluation index is used for ranking. It is also necessary to make a choice in order to make it easy for anyone to handle.

Taking the above ranking process one step further, in order to maximize the target profit and loss, ranking by adding the process of storing the evaluation index as a variable, the process of finding the optimum solution, and the process of displaying it. The process evolves into a ranking process based on AI learning using machine learning.

If you decide the target profit and loss using the trading data, you will learn which ranking target and which evaluation index should be ranked to promote changes in investor behavior in an easy-to-understand manner, or whether it is optimal, and the ranking target Learn the inferior points compared to trading data. By displaying the learned results, the AI ranking process will allow AI to find the optimal solution.

Also, as a news article, it is desirable if the goal is to automatically generate popular ranking articles based on the access status. Of course, it is necessary to consider privacy, and if access is overemphasized, strange articles will be generated by the information processing system, so it is desirable to operate while setting strict rules. In the case of automatic distribution of ranking articles using trading data, if the trading data is updated in one day, new information will be provided at any time, so articles with news characteristics will be generated by the information processing system. In today's event (news), the people who own this brand can also automatically generate articles about how they behaved by the information processing system. In the trading data to be aggregated by investment target, set "Extraction condition: Stock = relevant stock" and set the AND condition of "Period = Today", and set the target profit and loss as trading profit and loss, and the trading set that bought and sold this stock yesterday and today is specified. Will be done. If the evaluation index is the number of trades, it is possible to rank the number of trades, and if the evaluation index is the amount of trade profits, it is possible to rank the earned people (there is a problem in compliance). Once the news is delivered, it is possible to create a mechanism that can automatically generate these articles by the information processing system by using this news delivery as a trigger.

(Action of AI ranking process)
In addition to the ranking process described above, once the target trading data and the target profit / loss are determined, in order to improve and optimize the target profit / loss, which evaluation target and which evaluation index should be used. Optimal by learning whether it is possible to optimize the ranking and displaying the evaluation index to be changed and how to change the evaluation index. It will be possible to make transactions that bring you closer to a clear solution. In addition, if the number of access to the article is added to the data item, the article can be automatically delivered according to the number of access.

(Significance of AI ranking process)
In addition to the ranking process described above, we will add a process to learn how profit and loss will change if the evaluation index is changed. A storage unit that stores it, an evaluation index that is a variable, a target profit / loss, target trading data (aggregated trading data and component trading data), a learning unit, etc. The structure and learning method are the objects of the invention.

(Effect of AI ranking process)
By adding the AI process in addition to the above-mentioned ranking process, it is effective to perform machine learning on how to rank the target trading data as the optimum solution.

(Specific example of AI ranking process)
(Specific example A)
For example, if you want to improve Mr. A's total profit and loss, create Mr. A's total profit and loss data, create total profit and loss level trading data (even if you have it in the previous process), and evaluate it as a component of total profit and loss. With the index as a variable, in order to optimize with the goal of improving Mr. A's total profit and loss, we will learn which ranking target and which evaluation index should be ranked, and whether it is optimal. The winning profit margin is the best for ranking, and if you change the winning profit margin from the current 4% to 20% with the goal of buying and selling the person with the highest winning profit margin, you can buy and sell 1 million yen in one year. One example is how many patterns are displayed, such as an increase in profit with a probability of 80%, and the target is a combination with a high probability and a large degree of change.

(Specific Example B)
For example, if you want to improve the trading profit / loss of A stock, you can create the trading data to be aggregated for A stock, create the component trading data for each investor, and target the trading profit / loss level trading data for A stock. Trading profit / loss data is collected for each investor. The trading profit / loss level of the A issue Various evaluation indexes that affect the trading data are calculated by the information processing system, and the influence of these various combinations on the trading profit / loss is learned. Furthermore, we will learn about the holding period and trading profit rate of issue A, the trading profit rate and average holding period of the person who has the highest trading profit, and what are the top trading profit and loss rankings of brand A? By showing whether you are buying or selling, which evaluation index is strong, and how it differs from the user's evaluation index, you can get suggestions for raising the ranking.

(Generation method by the information processing system in learning AI ranking)
(Purpose)
We will learn which ranking target and which evaluation index should be used as the basis for ranking to improve the target profit and loss.

(Steps of learning generation method of AI ranking process)
The procedure for creating aggregated trading data and component trading data, the step for deciding which profit / loss to improve, the step for calculating the evaluation index that constitutes the profit / loss by the information processing system, and the ranking target. There is a calculation step for calculating a changing profit / loss by combining the original trading data and the evaluation index calculated by the information processing system.

Learn what combination is the best solution, determine which target and which evaluation index should be used for ranking, and raise the overall profit / loss ratio of Mr. A. The theme is which ranking target should be referred to, and the total profit / loss ratio of Mr. B and the values of various evaluation indexes that compose it, and the total profit / loss ratio of Mr. C and that compose it. We will learn whether the values of various evaluation indexes, the total profit / loss ratio of Mr. ZTT and the values of various evaluation indexes that compose it are optimal for each ranking. Among them, Mr. ZA is the most suitable as a ranking target, and by referring to those trading methods, brands, trading periods, etc., it can be expected that the improvement path will be clarified.

In the ranking of winning percentages, even if there are not many discoveries, it is possible for AI to judge in the learning generation step of this AI comparison process that there are various suggestions that the ranking is for each issue of winning profit margin.

(Definition of ranking based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
To give an example of ranking using the information processing system based on the trading data by component with the investment target of the trading data to be aggregated by investment target as a component, evaluation of trading profit / loss ratio or unrealized profit / loss ratio for each stock. Ranking by index can be mentioned. An example is the case where ~ (investment target) is ranked by ~ (investment target) by the evaluation index (calculated by the information processing system under the relevant conditions). One specific example is ranking the stocks by the total profit / loss ratio for each investment product such as stocks and virtual currency by the information processing system, and ranking the stocks by the trading profit / loss ratio or winning rate by brand in the information processing system. Is.

(The effect of ranking based on the trading data by component, which is the component of the investment target of the trading data to be aggregated by investment target)
Based on the trading data to be aggregated, the investment target is processed by the information system under the conditions such as extraction conditions, classification conditions, or aggregation rules, and further extracted, classified, or aggregated according to the investment target, and the profit / loss level. By ranking with the evaluation index calculated by the information processing system based on the trading data further processed in, the information based on the trading data by component with the investment target of the aggregated trading data by investment target as the component. Ranking in the processing system becomes possible. The ranking target may be the ranking of trading data for each stock in the stock, or the stock group of the stock may be ranked by the winning percentage.

(Effect of ranking by trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
The ranking is based on the actual trading data of the stocks, and has the effect of enabling multifaceted comparisons that cannot be compared with the usual stock rankings. For example, "A stock that you own has a low win rate of 15% in September, and the win rate ranking is 3500 out of 3900 stocks, which means that everyone is struggling." Is possible. Aggregation target trading data by investment target by the information processing system Aggregation target trading data by investment target It can be said that the content is unique to the ranking based on the trading data by component, with the investment target as a component.

(Specific example of ranking based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
Among the stocks, ranking each evaluation index of the stock group, calculating the trading profit / loss rate, winning rate, winning profit rate, unrealized loss rate, etc. with the information processing system, and displaying the ranking result is one of the specific examples. It is one. ..

(Definition of ranking based on trading data by component with investors as components of trading data to be aggregated by investment target)
To give an example of ranking by component trading data with investors as components of the trading data to be aggregated by investment target, the trading profit / loss ratio calculated by the information processing system for the trading of investors in the trading of stock A Ranking by evaluation index such as unrealized profit / loss ratio can be mentioned. An example is the case where ~ (investment target) is ranked by the information processing system by the evaluation index (calculated by the information processing system under the conditions) for each (investor). One specific example is ranking the stocks by the information processing system based on the total profit / loss ratio of investors in the buying and selling of stock A, and ranking the stocks by the trading profit / loss ratio or winning rate by the information processing system for each investor.

(The effect of ranking by the trading data by component with the investor as the component of the trading data to be aggregated by investment target)
Based on the trading data to be aggregated, the information processing system narrows down the investment targets by extraction conditions, classification conditions, aggregation rules, etc., and further extracts, classifies, or aggregates the trading data by investor, and profits and losses. By ranking with the evaluation index calculated by the information processing system based on the target trading data further processed at the level, it is based on the trading data by component with the investor of the target trading data aggregated by investment target as the component. Ranking is possible. The target of the ranking may be the ranking of the trading profit / loss ratio of the investors in the trading of the A brand, or the stocks may be ranked by the winning percentage of each investor.

(Effect of ranking by trading data by component with investors as components of trading data to be aggregated by investment target)
The ranking is based on the information processing system based on the actual trading data of the brand, which has the effect of enabling a concrete and unprecedented ranking. For example, in the buying and selling of stocks in 2020, Mr. A can express that this evaluation index is 100th out of 15,000 people and this evaluation index is 900th.

(Specific example of ranking based on trading data by component with investors as components of trading data to be aggregated by investment target)
Create investment groups that are divided into groups such as excellent-performing investor groups, medium-performing investor groups, and poor-performing investor groups, and rank them according to evaluation indicators. It is one of the concrete examples to calculate by the information processing system and display the ranking result.

The first step is a trading data acquisition step, followed by a trading data creation phase. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component. The fourth step is the step of creating profit / loss level trading data. The fifth step is a calculation and selection step of the evaluation index by the information processing system. The operation phase is a phase of "what to do" using the evaluation index extracted and selected in the fifth step, and the order relationship with other steps does not matter.

The sixth step is an evaluation step. The seventh step is a comparison step. The eighth step is a ranking step. The ninth step is this step, and the diagnosis step is defined as the comprehensive judgment of the evaluation step, the ranking step, and the comparison step. Displaying the contents diagnosed in the diagnostic step in a diagnostic report, table, graph, etc. is defined as the diagnostic display process.

(What is diagnosis)
The term comes from a doctor examining a patient to determine his or her medical condition, but here it is to find out where in the obtained endpoints the defect is.

(Issues in the diagnostic process)
How is it compared to others for investors, and what is inferior to the average and the best performing? It is difficult to compare such items at present, and it is difficult to judge where the defect is and the profit and loss will not improve.

(Action of diagnostic process)
Diagnosis is facilitated by following the process as shown in the definition of diagnostic process. Through the comparison process, ranking process, and evaluation process, it is possible to clarify the defects found and determine which evaluation index is worse than others. In order to clarify the defect, the evaluation index below the average is limited by comparison with the average value of the evaluation index, and the ranking is based on the evaluation index to determine the ranking. In particular, there is one way to identify indicators that are inferior to others.

(Effect of diagnostic process)
In this diagnostic process, you can see which evaluation index should be targeted for improvement.

(Specific example of diagnostic process)
In the diagnosis result of Mr. A, each evaluation index is calculated by the information processing system, the average value of each evaluation index is calculated by the information processing system, the deviation rate from the average value is calculated, and the deviation rate is calculated. It is also an example to give a diagnostic result that identifies an evaluation index with a large negative value (inferior to the average value) as an evaluation index with a large room for improvement.

(New method of AI machine learning diagnostic process)
The AI machine learning comparison process is performed through the following process.

The first step is the process of creating trading data to be aggregated. The second step is the creation of component trading data (optional). The third stage is the process of creating a profit and loss level evaluation index (calculating the target evaluation index by three methods). Up to this third stage, the target profit and loss and the target trading data are determined.

In the fourth stage, the information processing system calculates an evaluation index that affects the target profit / loss (total profit / loss, trading profit / loss, etc.) determined in the third stage. The fourth stage can be included in the third stage or can be another stage (optional). Up to this fourth stage, the target profit and loss, the target trading data (data structure), and the evaluation index that is a variable are determined.

In the fifth stage, a comparison step, a ranking step, and an evaluation step are performed with the trading data, the target profit / loss, and the evaluation index calculated by the information processing system. The sixth step is to learn and memorize these results and identify which metrics should be emphasized (s) in order to improve the target profit and loss. The seventh stage is a display step for creating a report, a table, a graph, etc. that summarizes these processes as a diagnosis result.

(Issues in the AI diagnostic process)
In the above-mentioned diagnostic process, there is a problem that there are many options to decide which ranking target is used, who is compared with whom, which profit / loss is diagnosed, and which evaluation index is used.

Going one step further from the above diagnostic process, in order to maximize the target profit / loss (the target determined in the third step), the target profit / loss that changes when the variable is changed with the evaluation index as a variable, By adding the process of memorizing variables when they change, the process of finding the optimal solution by which variable is efficient, and the process of displaying it, the diagnostic process makes machine learning. It evolves into a diagnostic process based on AI learning using it.

If you decide the target profit and loss using the trading data, you will learn which diagnostic result should be the best, and learn the inferior points compared to other trading data. By displaying the learned results, the AI diagnostic process will allow AI to find the optimal solution.

(Action of AI diagnostic process)
In addition to the above-mentioned diagnostic process, once the target trading data and the target profit / loss are determined, which evaluation target should be improved and how should it be improved in order to improve and optimize the target profit / loss. By learning whether it can be optimized or not, and displaying the evaluation index to be changed and how to change the evaluation index, a transaction that approaches the optimum solution. Will become possible.

(Significance of AI diagnostic process)
In addition to the above-mentioned diagnostic process, a process is added to learn how profit and loss will change if the evaluation index is changed. A storage unit that stores it, an evaluation index that is a variable, a target profit / loss, target trading data (aggregated trading data and component trading data), a learning unit, etc. The structure and learning method are the objects of the invention.

(Effect of AI diagnostic process)
By adding the AI process in addition to the above-mentioned diagnostic process, it is effective to perform machine learning on how to diagnose the target trading data as the optimum solution.

(Specific example of AI diagnosis process)
(Specific example A)
For example, if you want to improve the total profit and loss of Mr. A, create the trading data to be aggregated by Mr. A, create the total profit and loss level trading data (you can have it in the previous process), and the factors that affect the total profit and loss. With the evaluation index as a variable, we will learn which evaluation index should be improved and which one is optimal in order to optimize it with the goal of improving Mr. A's total profit and loss. It can be diagnosed that the winning profit margin is the most suitable for diagnosis, and for that purpose, it is necessary to change from the selection of the brand. Among the stock selections, the Y stock has a higher average trading profit margin and the winning profit margin is higher than the A stock, so it may be urged to select such a stock. Presenting a stock ranking with a high winning profit margin may be displayed as one result.

If it is judged that it is optimal to aim at improving the unrealized loss rate, several patterns are displayed, such as providing the diagnosis result that it is important to change the current holding situation, and the probability is high and the degree of change is high. Aiming for a large combination is an example.

(Specific Example B)
For example, if you want to improve the trading profit / loss of A stock, you can create the trading data to be aggregated for A stock, create the component trading data for each investor, and target the trading profit / loss level trading data for A stock. Trading profit / loss data is collected for each investor. Trading profit / loss level of stock A Various evaluation indexes that affect trading data are calculated by the information processing system, and the influence of these various combinations on trading profit / loss is learned, and the holding period of stock A and the holding period Learn about the trading profit margin, the trading profit margin and average holding period of the person who has the highest trading profit, and compare and rank which number to improve among the many indicators. Including, we will provide the diagnosis results.

(Learning generation method of AI diagnosis)
(Purpose)
We will learn which aggregation target and which evaluation index should be improved to improve the target profit and loss.

(Steps of learning generation method of AI diagnostic process)
Based on the procedure for creating aggregated trading data and component trading data, the step for deciding which profit / loss to improve, and the step for calculating the evaluation index that affects the profit / loss by the information processing system. Learn how to calculate the changing profit and loss by combining the trading data and the evaluation index calculated by the information processing system, and what kind of combination is the best solution, and what kind of diagnosis should be done. The theme is which diagnostic result should be presented in order to judge whether there is the greatest room for improvement and to raise the overall profit / loss ratio of Mr. A, and whether the diagnostic result is optimal or not. I will learn.

(Significance of diagnostic process)
The information generation unit 3021 calculates an evaluation index from the aggregation target trading data, diagnoses the aggregation target with the evaluation index, and displays a report of the diagnosis result on the display unit 23 of the terminal 2. Diagnosis is a process of grasping the holding and buying / selling status of the aggregated object by using a profit / loss level evaluation index or the like, and obtaining useful information for advice.

(Issues in the diagnostic process)
Diagnosis of investment products includes diagnosis using technical indicators, performance indicators, etc., but diagnosis using profit / loss level evaluation indicators has completely different effects.

For example, stocks that many people have unrealized losses, stocks that are profitable in short-term trading, stocks that are rapidly increasing in number of people who have unrealized losses, how to strengthen the winning pattern, etc. Various diagnostic results of investors will be obtained. The same applies to the diagnostic results of investors, the diagnostic results of virtual currencies, etc., and various components and aggregate targets are diagnosed from the aggregated trading data. It is the diagnostic result of the diagnosis target that appears as a result of various trading, and since these are derived starting from the analysis result of the trading data, the diagnostic result comes out from the actual trading result.

(Means of diagnostic process)
In the information presentation system 10, the information generation unit 3021 calculates a profit / loss level evaluation index, and uses the evaluation index to display the diagnosis result of the holding status and the trading status of the aggregation target on the display unit 23 of the terminal 2.

(Effect of diagnostic process)
The information generation unit 3021 diagnoses the holding status and the trading status of the aggregation target or component by using the profit / loss level evaluation index. The information generation unit 3021, for example, states that "A stock has a high trading profit margin, a high unrealized profit margin, and many people are making profits. In particular, the longer the holding period, the larger the unrealized profit, and short-term trading. Profit margin is also relatively high. ”Provides diagnostic results for each stock. The information generation unit 3021 said, "Mr. A has a high trading profit margin, a high unrealized profit margin, and a high profit. Especially for stocks with a long holding period, the unrealized profit is expanding, and the short-term trading profit margin is also relatively high. Providing diagnostic results for each investor, such as "."

In the diagnostic process, using multiple profit and loss level evaluation indicators, etc., comprehensively judge the trading status and holding status of the aggregated target, grasp the good points and bad points, and improve the bad points with advice. It is the process of making decisions to develop good points. There are various diagnostic targets such as not only investors and stocks but also commodities, stock groups, investor types, and investor groups.

(Specific example of diagnostic process)
As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated by the data set, and an evaluation index according to the purpose is calculated. Therefore, even in this step, the target can be easily diagnosed under various conditions and various forms of evaluation indexes. Although this step is only one step in FIG. 102, since the evaluation target and the evaluation index have been determined by a series of cooperation, the evaluation target mentioned in the present specification can be used in many forms of the evaluation index. Diagnosis is possible.

(Significance of level-step diagnostic process)
The profit and loss level is divided into each level, and it is possible to make a multi-step diagnosis by diagnosing the aggregated object or component based on various profit and loss level evaluation indexes of the trading data at the target profit and loss level. can. Diagnosis performed at this profit and loss level enables deeper diagnosis in stages.

(Issues in the level-step diagnostic process)
For example, in the diagnosis of the trading profit / loss level evaluation index of the aggregation target or the component, the diagnosis such as the holding status of the aggregation target or the component is not performed. Multi-faceted and multi-step diagnosis is possible by calculating the evaluation index according to the profit and loss level from the overall profit and loss situation to the detailed profit and loss situation by the information processing system and performing the diagnosis.

(Necessity of level stage diagnostic process)
For example, the diagnosis of stock A based on the total profit / loss level is, for example, a shallow diagnosis that the average profit / loss ratio is 50% and many people are making a profit. On the other hand, when diagnosing up to the 4th level, 30% of the total are making unrealized profits in stock A, and most of them have been holding for more than a year, and they are frequently bought and sold, and profits are made by buying and selling frequently. Investors who are issuing stocks also have high turnover power, and it is possible to make more detailed diagnoses such as the annual rate of return exceeding 50%.

(Action of level stage diagnostic process)
The level stage diagnosis is performed by the following procedure. That is, the information generation unit 3021 makes a comprehensive diagnosis by calculating the total profit / loss level evaluation index, and makes a diagnosis using the second level unrealized profit / loss and the trading profit / loss level evaluation index, and the third level winning profit level and losing loss level. We perform from wide-ranging diagnosis to detailed diagnosis, such as diagnosis by divided levels. There are various trading methods and practices even for one tabulation target. Such diversely collected trading data cannot be accurately diagnosed unless it is multifaceted and multi-stepped based on the results of various profits and losses.

(Effect of level stage diagnostic process)
By performing multi-faceted and multi-step diagnosis on the trading data aggregated for each aggregation target, there is an effect that it becomes possible to accurately grasp the holding status and trading status of the aggregation target. .. Since a large number of profit / loss level evaluation indexes at each level are calculated by the information processing system by the level-step diagnosis, more detailed and deep diagnosis is possible in a wide range.

(Summary of diagnostic report automatically generated by the information processing system)
The diagnostic system automatically generated by the information processing system is a compilation of the results so far. The contents include various results, comparison results, ranking results, etc. obtained by holding status evaluation, including trading data creation methods such as various extraction conditions, target profit and loss, various evaluation indicators, KPIs, etc. , Display so that it can be displayed as a list.

(Problems of the conventional method)
In the third embodiment, there is a description of automatic generation in the comprehensive diagnosis report. In the information processing system, all information is linked to the database, so the linked data can be easily retrieved, and there are numerical data, text data, and table and graph data.

(Action of diagnostic report automatically generated by the information processing system)
For example, Investor A's 2020 diagnostic report is created by the following procedure. Extraction condition in the trading data to be aggregated by period: In 2020, if investor = investor A and target profit / loss = total profit / loss, the target trading data is specified. From there, evaluation indexes related to total profit and loss are calculated by various information processing systems. Among the evaluation indexes calculated by the various information processing systems, the KPI is determined. This information may or may not be included in the results report, but behind the scenes such a system is in operation. Then, the result of the holding status evaluation (various information of the holding stocks) and the result of the trading status evaluation become the core first, and the report is formed. A comparison report and a ranking report will be added to complete the diagnostic report. These are all done in cooperation with the system, not separately, and the problem is what to display and how to display it. This may be done in the display step or here. All numerical data and text are placed in appropriate places, and a diagnostic report generated by the information processing system is automatically generated.

(Effect of diagnostic system automatically generated by the information processing system)
The compilation of the past will be output in this report. Of course, the amount of information is enormous, and if it is not selected, the report will be difficult to read. Therefore, a mechanism that can be automatically generated by the information processing system while controlling the selection is desired. For the user, the administrator can immediately grasp the situation of Mr. A in 2020, and it is convenient for Mr. A to have such a comprehensive report. The data generated by these information processing systems is updated daily, so the content of today's and tomorrow's reports will change dynamically. By recording daily data in the storage unit 33, it is possible to easily compare the diagnostic report of one month ago and the current diagnostic report, and the diagnostic report automatically generated by the information processing system is highly convenient. Is a service unique to the information system that can be formed in conjunction with a consistent system.

(Specific example of diagnostic system automatically generated by the information processing system)
In addition to Mr. A's diagnostic report, if you change various conditions such as A brand diagnostic report, day training type diagnostic report, 2020 investment product diagnostic report, buying and selling diagnostic report by technical indicators, 2020 brand diagnostic report, etc. Since the number of diagnostic reports is automatically generated by the information processing system, a huge amount of diagnostic reports can be created if you want to make one. In reality, the indispensable ones are selected and the report is automatically created.

(Definition of diagnosis based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
To give an example of diagnosis using the information processing system based on the trading data by component with the investment target of the trading data to be aggregated by investment target as a component, evaluation of trading profit / loss ratio or unrealized profit / loss ratio for each stock. Diagnosis by indicators can be mentioned. When diagnosing ~ (investment target) by ~ (investment target) with the evaluation index (calculated by the information processing system according to the relevant conditions). Among stocks, the information processing system can be used to diagnose the total profit / loss ratio for each investment product such as stocks and virtual currencies, and the information processing system can be used to diagnose stocks by stock / profit / loss ratio or win rate. This is an example.

(The effect of diagnosis based on the trading data by component, which is the component of the investment target of the trading data to be aggregated by investment target)
Based on the trading data to be aggregated, the investment target is processed by the information system according to the extraction conditions, classification conditions, aggregation rules, etc., and further extracted, classified, and aggregated by investment target, and further at the profit / loss level. Based on the processed trading data, diagnosis is performed using the evaluation index calculated by the information processing system, and the information processing system is based on the trading data by component, which is the component of the trading data to be aggregated by investment target. It is possible to make a diagnosis in. The ranking target may be the diagnosis of trading data for each stock in the stock, or the stock may be diagnosed by the winning percentage for the stock group.

(Effect of diagnosis by trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
The diagnosis is made by the information processing system based on the actual trading data of the brand, and has the effect of enabling a multifaceted diagnosis that is incomparable to the usual brand diagnosis. For example, among the stocks, the A stock that we own has a low win rate of 15% in September, and the win rate ranking is 3500th out of 3900 stocks, which is quite a struggling stock, while the Z stock is 9 The winning percentage of the month is as high as 80%, and it is possible to express that it seems that we can fight for an advantage at the moment. Aggregation target trading data by investment target by the information processing system Aggregation target trading data by investment target It can be said that the content is unique to diagnosis based on the trading data by component with the investment target as a component.

(Specific example of diagnosis based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
Among stocks, it is possible to diagnose each evaluation index of the stock group, calculate the trading profit / loss rate, win rate, winning profit rate, unrealized loss rate, etc. with the relevant information processing system, and display the diagnosis result for each stock group. , Is one of the concrete examples.

(Definition of diagnosis based on trading data by component with investors as components of trading data to be aggregated by investment target)
To give an example of diagnosis using trading data by component with investors as components of trading data to be aggregated by investment target, the trading profit / loss ratio or unrealized profit / loss calculated by the information processing system for the trading of investors of brand A Diagnosis can be made using evaluation indicators such as rates. This is an example of the case where ~ (investment target) is diagnosed by the information processing system using the evaluation index (calculated by the information processing system according to the conditions) for each (investor). Diagnosis with the information processing system based on the total profit / loss ratio of each investor of issue A and diagnosis of stocks with the information processing system based on the trading profit / loss ratio and winning rate for each investor are one concrete example. This is an example.

(The effect of diagnosis based on the trading data by component with the investor as the component of the trading data to be aggregated by investment target)
Based on the trading data to be aggregated, the information information system narrows down the investment targets by extraction conditions, classification conditions, aggregation rules, etc., and further extracts, classifies, or aggregates the trading data by investor, and profits and losses. Based on the target trading data further processed at the level, diagnosis is performed using the evaluation index calculated by the information processing system. This makes it possible to make a diagnosis based on the trading data by component, with the investor as the component of the trading data to be aggregated by investment target. It may be a diagnosis of an investor's trading profit / loss ratio in the buying and selling of stock A, or it may be a diagnosis of stocks by an investor's winning percentage.

(Effect of diagnosis by component-specific trading data with investors as components of aggregated trading data by investment target)
The diagnosis is made by the information processing system based on the actual trading data of the brand, which has the effect of enabling a concrete and unprecedented diagnosis. For example, in the buying and selling of stocks in 2020, Mr. A has an unrealized profit margin of 100th out of 15,000 people, a trading profit margin of 900th, and the unrealized profit margin is overwhelmingly higher than the average, but he may miss the profit settlement. It is possible to express that there are many.

(Specific example of diagnosis based on trading data by component with investors as components of trading data to be aggregated by investment target)
Create an investment group that is divided into groups such as an investor group with excellent performance, a medium-performing group, and an investor group with poor performance, diagnose with an evaluation index, and obtain the relevant information on the trading profit / loss rate, winning rate, winning profit rate, and unrealized loss rate. One of the concrete examples is to calculate by the processing system and display the diagnosis result.

The first step is a trading data acquisition step, followed by a trading data creation phase. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component. The fourth step is the step of creating profit / loss level trading data. The fifth step is a calculation and selection step of the evaluation index by the information processing system. The operation phase is a phase of "what to do" using the evaluation index extracted and selected in the fifth step, and the order relationship with other steps does not matter.

The sixth step is an evaluation step. The seventh step is a comparison step. The eighth step is a ranking step. The ninth step is a diagnostic step. The tenth step is an advice step, and the eleventh step is a display step.

(Significance of the advice process)
In the information presentation system 10, the information generation unit 3021 calculates a profit / loss level evaluation index from the aggregated trading data, and outputs an advice result based on the diagnosis result, ranking result, comparison result, etc. using the evaluation index to the terminal 2. Is displayed on the display unit 23 of. The advice is to display the advice result using the evaluation result, the ranking result, the comparison result, the diagnosis result, etc. using the profit / loss level evaluation index and the like as judgment materials. The elements that make up trading data refer to dates, stocks (groups), commodities (groups), investors, investor types, investor groups, and so on.

(Issues in the advice process)
Advice for each investment product aggregation target or component includes technical indicators, performance indicators, etc., but diagnostic results, ranking results, etc. that diagnose the aggregation target or component using evaluation indicators obtained from trading data, Advice for each aggregation target or component based on comparison results, evaluation results, etc. has a completely different effect.

(Means of advice process)
In the information presentation system 10, the information generation unit 3021 causes the display unit 23 of the terminal 2 to display the advice result based on the diagnosis result, the ranking result, the comparison result, the evaluation result, etc. using the profit / loss level evaluation index.

(Effect of advice process)
The information generation unit 3021 displays the advice result from the diagnosis result, the ranking result, the comparison result, the evaluation result, and the like, the holding status and the trading status of the aggregation target or the component, using the profit / loss level evaluation index. By giving advice based on the diagnosis result, ranking result, comparison result, evaluation result, etc., it is possible to display the advice according to the situation of the aggregation target or the component.

(Specific example of advice process)
For example, "A stock has a high trading profit margin, is ranked 5th, has a high unrealized profit margin, is ranked 3rd, and there are many people who are making profits. In particular, those who have a long holding period have a longer holding period. The unrealized profit is swelling, and the rate of return on short-term trading is relatively high. ”We will provide advice to Mr. A based on the diagnosis results, ranking results, comparison results, etc.

"The trading situation of Mr. A's A stocks has a low trading profit margin, a low unrealized profit margin, and no profit. Compared to others, it is clearly inferior and there is a lot of room for improvement. First, A. Regarding stocks, it is recommended that you go to buy a squeeze, do not easily determine profits even if it rises, and keep holding for a little longer. " The information generation unit 3021 provides advice based on diagnosis results, ranking results, comparison results, etc. for each investor and investment target.

As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated, and an evaluation index according to the purpose is calculated. Therefore, even in this step, it is possible to easily advise the target under various conditions and various forms of evaluation indexes. Although this step is only one step in FIG. 102, since the evaluation target and the evaluation index have been determined by a series of cooperation, the evaluation target mentioned in the present specification can be used in many forms of the evaluation index. Advice is possible.

(New method of AI machine learning advice process)
The AI machine learning comparison process is performed through the following process.

The first step is the process of creating trading data to be aggregated. The second step is the creation of component trading data (optional). The third stage is the process of creating a profit and loss level evaluation index (calculating the target evaluation index by three methods). Up to this third stage, the target profit and loss and the target trading data are determined.

In the fourth stage, the evaluation index, which is a component of the target profit / loss (total profit / loss, trading profit / loss, etc.) determined in the third stage, is calculated. The fourth stage can be included in the third stage or can be another stage (optional). Up to this fourth stage, the target profit and loss, the target trading data (data structure), and the evaluation index that is a variable are determined.

In the fifth stage, the diagnosis step is defined as the comprehensive judgment of the evaluation step, the ranking step, and the comparison step. In the sixth stage, the diagnostic step identifies the evaluation indicators to be improved, and by showing the actual results of the improvement of those evaluation indicators, it promotes changes in the user's trading behavior. It is this advice step to go.

In the sixth stage, it is the seventh stage to display how to display the advice result, which is the optimum solution, by an appropriate display method. Tables, pie charts, component ranking displays, ranking displays, etc. can be mentioned.

(Issues in the AI advice process)
In the above-mentioned advice process, there is a problem that there are many options for deciding which aggregation target is used, which profit / loss is to be advised, and which evaluation index is used to give advice.

Going one step further from the above-mentioned advice process, in order to maximize the target profit and loss, advice is given by adding a process of storing the evaluation index as a variable, a process of finding the optimum solution, and a process of displaying it. The process evolves into an advice process based on AI learning using machine learning.

If you decide the target profit and loss using the trading data, you will learn which advice result should be given, and learn the inferior points compared to other trading data. By displaying the learned results, the AI diagnostic process will allow AI to find the optimal solution.

(Action of AI advice process)
In addition to the above-mentioned advice process, once the target trading data and the target profit / loss are decided, which evaluation target should be improved and how to improve it in order to improve and optimize the target profit / loss. By learning whether it can be optimized or not, and displaying the evaluation index to be changed and how to change the evaluation index, a transaction that approaches the optimum solution. Will become possible.

(Significance of AI advice process)
In addition to the above-mentioned advice process, we will add a process to learn how profit and loss will change if the evaluation index is changed. A storage unit that stores it, an evaluation index that is a variable, a target profit / loss, target trading data (aggregated trading data and component trading data), a learning unit, etc. The structure and learning method are the objects of the present invention.

(Effect of AI advice process)
By adding the AI process in addition to the above-mentioned advice process, it is effective to perform machine learning on how to give advice on the target trading data as the optimal solution.

(Specific example of AI advice process)
(Specific example A)
For example, if you want to improve Mr. A's total profit and loss, create Mr. A's total profit and loss data, create total profit and loss level trading data (even if you have it in the previous process), and evaluate it as a component of total profit and loss. With the index as a variable, we will learn which aggregation target, which evaluation index should be improved, and which is optimal in order to optimize with the goal of improving Mr. A's total profit and loss. Increasing the difference between the winning profit rate and the losing loss rate is the best diagnosis target, and the winning profit rate and the winning profit rate are aimed at buying and selling the first person with the largest difference between the winning profit rate and the losing loss rate. If the difference in the loss loss rate is changed from the current 2% to 30%, the trading profit of 1 million yen will increase with a probability of 80% in one year. If it is 10%, the trading profit of 300,000 yen will increase with a probability of 70%. By changing the target number, it becomes possible to show how much the target profit and loss will change.

(Specific Example B)
For example, if you want to improve the trading profit / loss of A stock, you can create the trading data to be aggregated for A stock, create the component trading data for each investor, and target the trading profit / loss level trading data for A stock. Trading profit / loss data is collected for each investor. Trading profit / loss level of stock A Various evaluation indexes that affect trading data are calculated by the information processing system, and the influence of these various combinations on trading profit / loss is learned, and the holding period of stock A and the holding period We will learn about the trading profit margin, the trading profit margin and the average holding period of the person who is making the maximum trading profit, and many of the people who are winning in the A brand purchased recently and continue to hold it now. If so, it is possible to judge that and show the success rate of holding the A stock with a probability.

(How to generate learning for AI advice)
(Purpose)
We will learn which aggregation target and which evaluation index should be improved to improve the target profit and loss.

(Steps of learning generation method of AI advice process)
The procedure for creating aggregated trading data and component trading data, the step for deciding which profit / loss to improve, and the step for calculating the evaluation index that constitutes the profit / loss by the information processing system are the basis. By combining the trading data and the evaluation index calculated by the information processing system, you will learn the calculation steps for calculating the changing profit and loss and what kind of combination will find the optimal solution.

The theme is which advice result should be presented in order to judge what kind of advice should give the most room for improvement and to raise the overall profit / loss ratio of Mr. A, and the advice result is. We will learn whether it is optimal or not. Mr. ZE, who has a high overall profit and loss ratio, learns why it is so high, shows a comparison with Mr. A, reviews the stocks he owns, and puts out a ranking of stocks with a high winning percentage and a stock with a high winning profit margin. It is possible to show the state of holding stocks with a low win rate and stocks with a high loss loss rate on average, and to give advice on reviewing the stocks held.

(Definition of advice based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
To give an example of advice based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component, the stocks held are 3500th out of 3900 stocks in the trading profit / loss ratio ranking, and a minus is recorded. While displaying on the information processing system that there are many people who are doing it, the information processing system informs the trading status and profit / loss status of other stocks with high performance and provides advice, or the winning rate of the stocks held is high among the stocks. If it is low, it is possible to propose a higher brand with the information processing system and provide advice. The information processing system provides advice using the evaluation index (calculated under the relevant conditions) of ~ (investment target) ~ (by investment target), shows the winning rate of stocks by brand, and raises the winning rate further. Providing advice in the above, showing the unrealized profit / loss ratio and winning profit margin for each stock, and providing advice in the relevant information processing system for the stocks held is one specific example.

(Problems of conventional technology)
Conventional investment advice includes advice on the composition ratio of stocks by FP, asset formation advice by investment advisors, stock advice, and advice on buying and selling investment trusts and stocks by securities companies. These are mostly due to intuition, knowledge, and experience, and have a strong personality, and there are great differences depending on the person. However, computer advice is high-level and quite difficult. Recently, robot advisors and the like have become widespread, and advice from robots is emerging. The advice provided by the information processing system is different from such advice, advice that has never been based on trading data, advice given by many investors as well as own trading data. This is advice that is given from various points of view in order to give advice based on the trading data.

(Action of trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
How do you actually provide the advice function in the information processing system? The information processing system generates various data such as comparison, ranking, display of evaluation index, diagnosis, etc. from evaluation of investment target on a daily basis. Not only the investment target, but also the results such as comparison, ranking, display of evaluation index, diagnosis, etc. are generated every day from the evaluation of investors. It moves with each transaction, and the information processing system produces different data. These data are recorded in the recording unit 33, and various advice data can be generated. When investor A decides to make an investment with a high probability of failure, the information system can calculate that the probability is low in the information system and tell him on the display screen of investor A. It is possible for the information system to determine and teach that everyone has a failed stock, there is a lot of selling pressure, and there are a lot of people who want to sell even if they return.

(Effects of trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
In most cases, the advice on investment products up to now is personal or even Roboad provides a portfolio such as ETFs that matches the investment experience and investment style of the user. Robot advisors on buying and selling individual stocks are more difficult than ETF portfolio advice. Because there are more options, price movements are volatile, and investment disparities are incomparably wide. In particular, trading advice using trading data, which is a dynamic concept, rather than a portfolio, which is a static concept, is a service that goes one step or two ahead. Specific examples of the generation of advice data have been scattered everywhere, and all of them generate consistent advice data unique to the information processing system.

(Specific example of trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
In terms of evaluation, advice data is studded in FIGS. 103 to 106, and many specific examples have been given for comparison, ranking, and diagnosis. These are various data to give advice so that the investor can make a better investment in the end, and since the data generated by the information system to guide the investor to make a better investment, the advice is given. Can all be used.

(Advice based on trading data by component with the investment target of the trading data to be aggregated by investment target as a component)
(Problems of conventional technology)
To give an example of advice based on trading data by component with investors as components of trading data to be aggregated by investment target, we give advice to raise Mr. A's ranking in the trading profit / loss ratio ranking of stocks purchased on 9/10. , Advice on the trading profit / loss ratio of the stock purchased on 9/10. The advice using the evaluation index (calculated under the relevant conditions) of ~ (investment target) ~ (component) is an example. One specific example is to show the winning percentage of stock A by investor and give advice to increase it, or to show the unrealized profit margin and winning profit margin of stocks by investor and give advice on stocks.

The first step is a trading data acquisition step, followed by a trading data creation phase. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component. The fourth step is the step of creating profit / loss level trading data. The fifth step is a calculation and selection step of the evaluation index by the information processing system. The operation phase is a phase of "what to do" using the evaluation index extracted and selected in the fifth step, and the order relationship with other steps does not matter.

The sixth step is an evaluation step. The seventh step is a comparison step. The eighth step is a ranking step. The ninth step is a diagnostic step. The tenth step is an advice step. The eleventh step is a display step (this time, this step).

(Meaning of display step)
For example, in response to the question of how to calculate the evaluation index that affected Mr. A's trading profit and loss, Mr. A's trading level trading data is extracted and aggregated, and the winning rate, winning profit rate, and losing loss rate are collected along with the trading profit and loss. , Etc. can be obtained by calculating with the information processing system. At this time, the winning rate can be automatically calculated from the trading level trading data, but the winning profit rate can be easily obtained by creating the winning level trading data. In this way, the necessary evaluation indexes are calculated by the information processing system, but there is a problem of the display method of how to convey these evaluation indexes of Mr. A. Among investors, there are various knowledge, experience, and know-how, and various display terminals. No matter how good the numbers, the good results, and the content to be improved, if it is difficult to understand or understand, it will be ruined. Display steps are set up to solve such problems.

(Issues of display steps)
The step is to display the evaluation index and the solution result calculated by the information processing system for the problem.

(Action of display step)
Even if it is calculated by the information processing system of the same evaluation index, how to solve the solution result in an easy-to-understand manner if it is displayed according to the evaluation index or problem is described in the problem, the evaluation index, the news, etc. It is required to display them together.

For that purpose, there are a method of making a table and a method of machine learning with AI. The method of creating a table and referencing it can be solved by creating a correspondence table for each of the different expression methods depending on the problem, evaluation index, extraction condition, classification method, aggregation method, and the like. A method may be used in which these corresponding functions are machine-learned and learned by AI to select the optimum display method.

(Effect of display step)
It takes a lot of time and effort to select and express various display methods each time. However, the table reference method can handle various cases. Radar chart for problem A, graph for problem B, table for problem C, items on the horizontal axis, items on the vertical axis, targets, etc., for example, evaluation index and year By doing so, you can expect a special effect that various display methods are possible.

(Specific example of display step)
(Specific example 1)
For example, in displaying the winning percentage of buying and selling by A stock in 2020, the winning percentage of A stock in 2020 was%, and the highest winning percentage in 2020 is%, not just the enumeration of the winning percentage of A stock in 2020. , It was a Z brand. The winning percentage ranking of brand A was 530th. It is easier to understand if you display it while entering specific numbers in the text.

In this case, in the case of a combination of year, brand, and winning rate, the winning rate of XX year and XX brand is XX% in the text display, and the maximum winning rate of XX year is XX%. did. You can calculate by deriving the stock with the highest winning percentage in 2020 by another calculation.

(Specific example 2)
To display the trading profit composition ratio (for each investor) of stock A in 2020, create trading data to be aggregated by investment target extracted by stock A, create component trading data by investor, and trade profit / loss level. Evaluation indexes etc. are derived by creating trading data (even if you have it in the previous process). However, even if the trading profit composition ratio for each investor of stock A is simply shown as 2% for investor A and 3% for investor B, it does not give a meaningful result.

However, the calculated trading profit composition ratio of A stock in 2020 is 20%, B stock is 15%, and 20 stocks are bought and sold in total in 2020, and the stock with a high trading loss composition ratio is G. If the pie chart shows that the stock has been pulled down by 20%, the user is very happy to get more information than to solve the problem. In order to be able to express this kind of expression, for the issue of what is the trading profit composition ratio of XX stocks in XX years, it is necessary to put out the trading profit composition ratio and trading loss composition ratio of other stocks together. , It is possible to display them as a pie chart by deriving them with a table reference. Of course, if machine learning is performed with AI, even more complicated processing becomes possible.

(Specific example 3)
The stock price chart is suitable as a display method for the trading data to be aggregated by issue, and it is an excellent display method to express the actual trading of Mr. A on the stock price chart. For the issue of wanting to know the trading profit / loss ratio of A stock by investor, the stock price chart of A stock can be used as a display method to plot the purchased stock price, sold stock price, its set and profit / loss by investor, or data. It is possible by displaying it.

(Specific example 4)
As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated, and an evaluation index according to the purpose is calculated. Therefore, even in this step, it is possible to easily display various conditions and various forms of evaluation indexes in various expression methods. Although this step is only one step in FIG. 102, since the evaluation target and the evaluation index have been determined by a series of cooperation, the evaluation target mentioned in the present specification can be used in many forms of the evaluation index. It can be displayed in many display methods.

(Significance of trading data linked chart display)
-Regarding trading data linked charts, ordinary stock price charts are linked to stock information. There are charts that have the function of presenting corporate performance, technical indicators, event information, etc. However, there is no chart that presents information on various trading in conjunction with trading data. Trading data refers to all information related to purchased stocks such as purchase date, purchased stocks, holding period, selling date, and market value of holding stocks.

(Conventional issue)
The conventional chart display is biased toward the brand information, and the method of linking with the brand information is the main.

(Action of trading data linked chart display)
On the other hand, the trading data-linked chart refers not only to the purchase date and the purchased issue, but also to the general method of displaying information associated with the holding period, the rate of increase / decrease after the purchase of the owned issue, and the like. In the case of the holding period, for example, if the holding period of the stock has passed 20 days, the price movements of the stocks currently held 20 days after the purchase date and 20 days after the purchase date are the current price movements. It is also a form of this trading data-linked chart that shows the rate of increase / decrease ranking of what would have happened if you had bought other stocks, and presented the price movements of other stocks with the same theme from the purchase date to the holding period. The trading data interlocking chart presents information linked to trading data, such as knowing how long the average holding period of other investors who purchased the same stock at the same timing during that period.

(Effect of trading data linked chart display)
Information linked to stock information is generally displayed together with stock information, such as corporate performance or stock price information, but information linked to trading data is various, such as holding period and winning rate. It will be the information linked to the evaluation index. If this information can be displayed on the stock price chart, the user can display that the winning rate is poor for the trading method that has failed based on the behavior of other investors and the trading tendency so far. It has the effect of being able to provide unprecedented information.

(Specific example of trading data linked chart display)
In addition to the methods listed above, there are methods such as those listed in FIGS. 103 to 106 based on the current holding status of the stocks held.

The first step is a trading data acquisition step, followed by a trading data creation phase. The second step is the step of creating the trading data to be aggregated. The third step is a step of creating trading data for each component. The fourth step is the step of creating profit / loss level trading data. The fifth step is a calculation and selection step of the evaluation index by the information processing system. The operation phase is a phase of "what to do" using the evaluation index extracted and selected in the fifth step, and the order relationship with other steps does not matter.

The sixth step is an evaluation step. The seventh step is a comparison step. The eighth step is a ranking step. The ninth step is a diagnostic step. The tenth step is an advice step. The eleventh step is a display step. The twelfth step is an article automatic generation step (this step).

(Definition of article automatic generation step)
The information processing system generates various information. Advice data and diagnostic data are rather useful when individual investors use individual trading data, but since the system handles trading data, various other information will be generated. How individual investors buy and sell is often featured in magazines as a successful example. However, it is biased toward some information, and the fact is that most of the information that appears in the world is success cases, and failure cases and average figures have not appeared in the world. Among the information generated by the information processing system, the data of the evaluation index generated by the information processing system from the ranking information, the trading data subject to aggregation by period, the trading data subject to investment target aggregation, etc. are described in various articles. Contains a lot of information that can also be used for distribution. It is clear from the description of the embodiments so far. From the perspective of this article distribution system (article data generation system), the article automatic generation step of the twelfth step is taken.

(Problems of conventional technology)
Regarding the automatic article generation system, Japanese Patent Application No. 2020-157142 states that the content of articles automatically generated for announced financial results, etc. will be focused on the characteristic matters included in the content of the announcement. Documents that are automatically generated according to the announcement of financial results such as are described. Articles that are automatically generated based on financial information, stock price information, financial information, etc., focusing on the characteristic items included in the content of the announcement. It is a generation system. The main purpose of this system is to catch the announcement of corporate performance as soon as possible, especially the upward revision range (the size of the divergence rate between forecasts and actual results (10, 13) and the size of the divergence rate higher than the past figures (14)). It is a system that automatically generates articles that can appeal the high degree of attention by automatically focusing on the characteristics of stocks with a large divergence rate compared to other companies (15).

(72) and (73) also include descriptions of the rate of return on corporate performance. However, this article generation system does not mention transaction data at all. It is a technology that focuses on revision announcements of corporate performance, which is likely to have a large impact on stock prices, and it is possible to automatically generate articles based on the fact of announcement of corporate performance announcement, but this conventional technology Has a big challenge. It is not known how investors will take investment behavior after the announcement of corporate performance and how the announcement of business performance will affect the investment behavior of investors. The information processing system can generate articles on how investment behavior has been taken based on actual investment behavior. Of course, it is not limited to the announcement of business results such as upward revision.

(Action of article automatic generation step)
In the information processing system, for example, what are the 10 best stocks whose business results were announced in September 2020 and which had the highest trading profit margin (stocks that made a profit in actual trading behavior)? It is a system that can automatically deliver articles such as. It is a technology that is ahead of the conventional technology, and is an epoch-making information processing system that can report and distribute the investment behavior of investors after the announcement of corporate performance. This distribution is a series of creation of trading data by the technology of trading data subject to aggregation by period, creation of trading data by component, determination of trading data set by creating profit and loss level trading data, and calculation of evaluation index. Cooperation is important, and it becomes the article data that is produced for the first time. Of course, the evaluation index is automatically generated as a numerical value generated from the information processing system, and the generated data can be used for display and article distribution.

Explaining how to realize the above flow, first, we give an instruction to create the aggregate trading data for each period of September 2020 of profit and loss level trading data with the information processing system, and announce the stocks and business results that are the components. Stocks with or without performance announcement (events are set as component items and managed by check items with and without performance announcement) are extracted from the component trading data, and evaluation indexes such as trading profit are calculated for each trading data. Then, the trading profit ratio is obtained by calculating the average value for each issue and displaying the average trading profit / loss ratio in the ranking. Everything works in tandem, and it is a technology that has taken a step or two.

(Effect of article automatic generation step)
Announcement of corporate performance has an impact on stock prices, but if this goes too far, investment behavior will go wrong. In other words, funds are concentrated on the stocks that are likely to be revised upward on the day or the day before, speculative funds aimed at upward revision flow in, and stocks that are likely to be revised downward are sold at once. It may be a cause. It is moving in a direction different from what was expected at the time to encourage speculative behavior. The main reason for this is that the actual investment behavior is still invisible. Because it is invisible, it leads to suspicion, speculative behavior, and crazy investment behavior. According to the information processing system, it is expected that the actual investment behavior will be visualized and such speculative behavior will be subsided. After all, investment and speculation are different, speculation progresses to gambling and only some users can utilize it, but with investment, many people can participate with peace of mind, and the flow from savings to investment It is a technology and an invention that can contribute to strengthening.

(Specific example of article automatic generation step)
The previous article, such as the 10 best stocks with the highest return on investment (average ROI) among the stocks whose business results were announced in September 2020, can be found in the information processing system even if the time changes. It can be automatically generated by changing the parameters. This is a technique that can be done because the technology of trading data subject to aggregation by period is effective, and without the trading data subject to aggregation by period (completed version), correct data will not come out, and it is called the trading profit / loss ratio (average). The evaluation index is also data that is generated by the information processing system through a series of linkages. In addition, the specification also gives many concrete examples of the generation of article data.

As shown in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, the necessary evaluation index can be calculated by the data set, and the evaluation index according to the purpose is calculated. Even in this step, various article data can be easily generated under various conditions and various forms of evaluation indexes. Although this step is only one step in FIG. 102, since the evaluation target and the evaluation index have been determined by a series of cooperation, the evaluation target mentioned in the present specification can be used in many forms of the evaluation index. It is possible to generate a large number of article data.

(Manage articles in the generated data management table)
By creating a generated data management table, these article data can be centrally managed from how the generated generated data was created, how it was displayed, and how it was used. It will be like. The generated data management table includes at least the generated data ID and the distribution method (there is also management in another table), and only how the data generated by the information processing system is displayed by associating all of them. Instead, it will be possible to manage how the generated data is accessed from the market and how popular it is. For example, the information processing system can generate generated data such as an evaluation index for all investors, a comparison between stock investors and virtual currency investors, and analysis of the current situation of US stock investors.

(How to use it as a problem solving system)
(Definition of problem solving system)
The information processing system is an information processing system that inputs trading data and generates various information as described above through the processes of the second step to the twelfth step. This process is a process of generating data such as advice. On the other hand, if you turn it over, it is also a system that can solve various investment issues.

In response to the question, for example, which stock had the highest average trading profit margin (average ROI) in 2020, the information processing system is stock A, and the average trading profit margin of investors is 75. %was. It has a structure that can solve various investment-related issues. Various investment issues can be solved by generating information on investor trading data using the system. For example, the task of calculating the winning percentage is also provided in Embodiment 1. It is a data generation system such as advice that derives the data of what percentage the winning percentage is from the trading data, and other indicators can be calculated in the same way. Then, these data are stored not only in the data itself but also in the storage unit 33 together with the diagnosis result and the working method (see FIG. 2). Using these memorized data, on the contrary, the question from the perspective of problem-solving means is to answer the question of what percentage of Mr. X's winning percentage is at the request of investors and managers. It is an information processing system. The more accumulated, the more it becomes possible to answer various tasks. For example, in response to the question of what percentage the winning percentage of Mr. A is, it is sufficient to create trading data from the trading data and obtain the winning percentage. It can be easily done even in the first embodiment. First, it is sufficient to determine what kind of extraction method is used to extract the trading data, which profit / loss is targeted, and which trading profit / loss level evaluation index should be calculated. The information processing system has both an aspect as a problem-solving means and a data generation system such as advice, depending on whether the work is decided for the problem or the work is calculated after the work is performed.

The work required from this question depends on the question. In the case of the trading profit / loss ratio, information is generated by creating trading data from the trading data, calculating the trading profit / loss ratio of each trading data, and calculating the average trading profit / loss ratio.

The part that derives various results from the trading data is abundant in the above-mentioned examples of the first and fourth embodiments, such as evaluation, calculation / display of evaluation index, comparison, ranking, diagnosis, and advice. On the contrary, these are the answers that come out when you inquire. For example, if you generate information that Mr. A's winning percentage in 2020 was 52%, and if Mr. A or the manager asks what the winning percentage of Mr. A in 2020 is, the latter is more useful. Widen the width.

Once the inquiry is decided, the answer is decided. Once the answer is decided, it is related to how to work from the trading data to reach the answer. Once the answer is decided, the information processing system will be more effective by accumulating and incorporating the part where the work is decided in the storage unit first. In other words, by simply asking a question in the first step from the first step to the twelfth step described above, the information processing system starts running for the result and generates information, thereby making it a more convenient information processing system. Become. Every day, ranking data, comparison data, evaluation data, diagnostic data, advice data, evaluation index data, etc. are generated by the information processing system. These generated data can be utilized not only by the input person of the trading data but also by the request of the manager, the user, and the user. When an investor asks for advice, he or she can answer it or use the advice generation when a user (including an administrator) wants to solve an investment problem. When the administrator generates a blog article, it can be dealt with by extracting the ranking table from the DB. Of course, the same goes for creating news articles.

FIG. 89 is a diagram showing a table reference method of the information processing process according to the fourth embodiment of the present invention. As shown in FIG. 89, data is generated, and the result is received and displayed, starting from input of trading data and transmission of request data (either an administrator or a user), and through various generation processes. For the generation system, follow the 11 steps described in the specification. Users (including managers) will be able to receive multifaceted advice regarding their own trading by inputting trading data. As shown in FIG. 89, based on one's own trading data, one can expect one's weaknesses, management, and improvement while managing comparison with others, ranking, and the like. The function of the information processing system as a problem-solving system is to be able to retrieve necessary data when necessary and receive various advice.

(Problems of conventional technology)
How do you derive the answer to the request from the user? Extract trading profit / loss level trading data for issues such as what kind of work should be done in response to questions from administrators and users, what kind of instructions should be sent to the information system, and what percentage of the above-mentioned winning rate should be. Then, if the number of winning trades (the number of trading profits) is divided by the number of trading, it can be calculated by the information processing system. This question has already been solved in the first embodiment. However, the skill level of general users is different from that of administrative users. Therefore, the problem of the user interface that makes it easy to make inquiries is also important. If the storage unit 33 has a memory of how the winning percentage is calculated, the work of how to calculate the winning percentage can be immediately performed by referring to the table in the information processing system. The more various evaluation indexes are calculated and various evaluations, comparisons, rankings, diagnoses, and advices are performed, the more the calculation procedure, diagnosis results, advice results, etc. are recorded in the storage unit 33, and conversely, this evaluation index is calculated. In response to the question of wanting to do so, the procedure can be easily extracted from the storage unit 33. That is, in both the first embodiment and the fourth embodiment, the combination of the question and the answer is accumulated in the storage unit 33 at any time. In the above example, the winning rate can be calculated by extracting trading data at the trading profit / loss level and dividing the number of winning trades (the number of trading profits) by the number of trading. It is the relationship between the work (calculation work such as the number of winning trades) and the result (calculation of winning percentage). The answer to how to calculate the winning percentage is to calculate the number of winning trades. Therefore, if the information processing system refers to the combination of work and result, it is possible to derive what kind of work should be performed as a combination table of result and work. In addition to the combination table of work and results, automation by AI using this storage unit 33 is also included. By learning from the work that such a result will be obtained, we will learn to do this work in order to obtain this result.

(Operation of problem solving system)
The idea of this task work combination table is the inside out that the task can be solved by doing the work. By incorporating it into the step of having work and solving the problem, it becomes possible to incorporate it into the step of having the problem and having the necessary work to solve the problem. If there is a table that combines the above-mentioned problem of what percentage of winning rate, creation of trading profit / loss level trading data, and calculation of the number of winning trades / number of trading, this problem can be solved immediately by the information processing system. .. In other words, if you contact the information processing system at any time, you know the work that can be extracted, so you can derive it. Trading profit / loss level If the information processing system performs the work of calculating the trading data, the number of winning trades, and the number of trading (calculation and extraction work), the problem of wanting to know the winning rate can be solved. Is understandable. Creating a table that summarizes the work and result tables makes the relationship between tasks and work clearer (see Fig. 91).

(Create a database of the generation process)
At the time of advice generation, article generation, and data request, the relations of the created generation process are stored in the table of 321-1 under certain conditions for the trading data at that time. Trading data extraction conditions, classification conditions, aggregation rules, trading data creation procedures, target profit / loss, evaluation indicators, actions (diagnosis, etc.) in action steps, generated contents, numerical data, etc. are sequentially recorded. .. For the same request, the same steps should be taken, but since the stock price and trading data are updated sequentially, the data is also updated. These updated data are also accumulated one by one. Since this step is taken when generating advice by badge processing, when generating articles, and when requesting data, the more time passes and the more it is used, the more data is generated in the DB under various conditions. go. Next, when the same task or request article is requested, the table data is searched from the storage unit and the determined rule is executed even if a new rule is not created. If you add a learning function here, machine learning will advance and you will be able to answer various complicated requests. Automation will progress through reinforcement learning. Working on the server is a similar step, so learning proceeds in the same way.

(Effect of problem solving system)
In the first and fourth embodiments, many investment issues and work methods for solving the investment issues are specified. So is the calculation of various evaluation indicators. An information processing system that brings in questions first, decides how to process trading data from the inquiries that the user has, and solves them has the effect of being easy for anyone to understand. Compared to the fact that you can solve various problems from trading data, look at this evaluation index to solve the problems that users have. Is easier to understand. It means the same thing, but it is the difference between the method of telling from the conclusion and tracing the cause and the method of going from the cause to the conclusion.

(Specific example of problem solving system)
(Specific example 1)
What is the winning percentage? The problem can be calculated by the information processing system from the trading profit / loss trading data by the number of wins and the number of trades (number of wins / number of trades).

(Specific example 2)
The problem of what percentage of the winning profit margin can be calculated by the information processing system by averaging the winning profit / winning purchase price from the winning trade trading data.

(Specific example 3)
The issue of what percentage of the unrealized loss rate can be calculated by the information processing system from the average of the unrealized loss / unrealized loss purchase price from the unrealized loss level trading data.

(Specific example 4)
To solve the problem of how many days the average number of days for trading is, the information processing system can calculate the number of trading days by calculating the number of trading days from trading profit / loss trading data and dividing by the number of trading.
These are the levels that are possible in the first embodiment, but the following cases are possible in the fourth embodiment.

(Specific example 5)
The issue of what percentage of the winning rate in 2020 is, create the trading data to be aggregated by period of Mr. A, create the trading profit / loss level trading data (even if you have it in the previous process), and the number of wins. / The number of transactions can be calculated by the information processing system.

(Specific example 6)
The issue of what percentage of the winning profit margin of Mr. A's A issue is to create the trading data to be aggregated by investment target of Mr. A's A brand, create the winning profit trading data, and from the average of the winning profit / purchase price. Can be calculated. If a series of these operations (creating trading data to be aggregated by investment target of Mr. A's A brand, creating winning profit trading data, total winning profit / average of purchase price) is performed in the information processing system, 2020 It means that anyone can calculate the trading profit / loss ratio of stock A in the year.

(Specific example 7)
For the issue of what kind of trading was done by the person who had the highest trading profit / loss ratio of A stock in 2020, the investor created the trading data to be aggregated by investment target under the extraction condition of A stock in 2020. It can be obtained by creating separately classified component trading data and ranking by the trading profit / loss ratio (total trading profit / loss / average of purchase price). In the fourth embodiment, various evaluation indexes can be calculated, but on the flip side, it is the information processing system that can answer various problems.

(Specific Example 8)
As described in FIGS. 101 and 102, if various conditions are added in FIG. 101, a data set according to the purpose is created, a necessary evaluation index can be calculated, and an evaluation index according to the purpose is calculated. Therefore, even in this step, various investment issues can be easily solved with various conditions and various types of evaluation indexes. Although this step is only one step in FIG. 102, since the evaluation target and the evaluation index have been determined by a series of cooperation, the evaluation target mentioned in the present specification can be used in many forms of the evaluation index. It is possible to solve many problems.

(Selection method and table reference method)
In order to meet the various needs of investors, it is one of the selection methods that the diagnosis result is displayed by clicking the diagnosis result using the trading data. The selection method referred to here clarifies this point.

(Overview of selection method)
In the case of a problem solving system or an article generation system, a result set (a combination of results for display and distribution on the terminal) is provided on the user terminal in response to a request for a problem or article from a user or an administrator. There are two methods, one is to have the request for an assignment or article selected and the other is to be input, and the latter has a table reference method and an AI method.

(Action of selection method)
Even with the conventional method, this selection method is possible (selection method by just displaying one button), but the simplest case is the selection method of content derived from Mr. A's trading data on Mr. A's terminal. Then, if you make a list and ask Mr. A to make a selection, your own diagnosis result will be displayed and the ranking result will be displayed. This is one of the selection methods. When Mr. A displays the list and asks him to select it, the result set is sent and displayed. For example, in the case of the selection method, the user terminal or the administrator terminal is made to select the issues or articles required by the user from the pull-down menu or in the list format, thereby selecting the extraction conditions and the like. Refers to a method in which the second to eleventh steps are executed and the result is displayed by executing. In this case, for example, in the case of creating trading data to be aggregated, the terminal has "extraction conditions: year, issue, investment type, etc.", "classification criteria: issue, investor", "aggregation criteria". By providing options such as ": for each brand", it is necessary for the user to make a selection.

(Definition of inquiry)
An inquiry is an issue to be solved related to an investment product, and refers to at least one of evaluation index comparison, evaluation index ranking, evaluation index display, evaluation index diagnosis, and evaluation index advice. For investors, knowing this will be a guidepost for problem solving (improvement of investment results). These inquiries are information generated by the information processing systems of the first and fourth embodiments. Of course, some of this information can be fully used as news articles and topical articles. FIG. 64 is a diagram of the relationship between the server and the terminal, but as the linkage with the database is also shown here, the relationship between the trading data and the evaluation index, the relationship between the question and the result, and, if turned over, advice, etc. Results and work procedures are accumulated sequentially (see Fig. 2).

FIG. 75 is a diagram showing a reference to a table of display methods of the information processing process according to the fourth embodiment of the present invention. That is, FIG. 75 is a reference diagram of the display table. Create a table that associates the evaluation index with the display method so that it can be displayed in a suitable and easy-to-understand manner. If the profit composition ratio of a stock is obtained from the evaluation index, a pie chart of the profit composition ratio with the stock name in a pie chart is more suitable than a simple list of composition ratios. In the case of "evaluation index = profit composition ratio of stocks", refer to this table and decide to display a pie chart. In addition to the evaluation index, by referring to the table that connects the display method with the operation such as issues, profit and loss, extraction conditions, advice, comparison, ranking, etc., it is possible to select the appropriate display method, and the display is easy to understand. It will be possible.

(Meaning of table reference method)
FIG. 89 is a diagram showing a table reference method of the information processing process according to the fourth embodiment of the present invention. If necessary, the required data is requested by the user or the administrator to the information processing system, and is expressed as a problem. The issue is transmitted, received by the information processing system, and the table is referred to. If the issue is in the table, the issue is referred to, otherwise it is recognized as a new issue, and a new condition is created. In the case of a new issue, conditions such as extraction, classification, and aggregation, profit / loss level, and necessary evaluation indicators are newly set. If it is an existing problem, by calling these conditions from the table and giving instructions to the information processing system, various trading data are created, evaluation indexes are calculated, and various operations are performed. In the case of a new task, commands such as conditions, calculated evaluation indexes, and actions to be executed are issued, and the next time the same task comes, the instructions are recorded in the table so that the instructions can be automatically read. This schematic is shown in FIG. 89.

As mentioned in the explanation of Fig. 71, by referring to the reference table, this relationship becomes clearer, it is possible to add more patterns, and it becomes easier to maintain the problem solving and the display of the result, and various things. You will be able to solve various problems. The flow from receiving trading data is the same as a normal information processing system. The method of extracting, aggregating, and classifying the trading data generated here is accumulated in the storage unit 33 each time, and the calculation of the evaluation index, the identification of the evaluation index, which operation (evaluation, comparison, ranking, diagnosis, diagnosis, advice). We will accumulate the history of whether or not the display was performed and how the display was performed (see FIGS. 2 and 42).

In the case of the table reference method, the issues and articles associated with the table and the extraction conditions are associated with the extraction condition table, etc., and for the issues and articles (requests) that have existed so far, the trading data is referred to. In order to create a table, the extraction conditions, classification conditions, and aggregation conditions are used, and if not, a new one is created to enhance the correspondence table. The table reference method is an important method when the input of issues and articles is not performed by the selection method or the management screen method, and plays an important role of connecting each step (first step to eleventh step). Fulfill.

(Important role of information generation table)
User and advice generation date, trading data extraction conditions, classification conditions and aggregation conditions, created trading data types, calculated evaluation indexes, what was done (whether it is a display of evaluation indexes or a diagnosis, comparison) It is a table that has data such as whether it is a ranking, advice), what kind of result (text of diagnosis result, etc.), etc. (If there are many items, the table may be divided). These pieces of information are data calculated by the advice generation system and are stored in the storage unit 33. However, in this reference table method, by managing them in a separate table, it becomes easier to refer to them later. The effect can be expected. This is an information generation table, and as mentioned earlier, this table is also an effective table for problem solving. In other words, if you explain what you did, for example, with a simple example of displaying the winning percentage, if there is data that displays the winning percentage in this table, the extraction conditions of the trading data used there and the created trading data You can immediately refer to the work procedure such as the type of. Therefore, the work procedure becomes clear from the problem of calculating the winning percentage, and a path for solving the problem can be established. As this table is enriched, the storage unit 33 will accumulate diagnostic results, advice results, calculation of various evaluation indexes, etc., and how to work with the information processing system in response to a large number of inquiries. The procedure of whether it is good is accumulated.

(Problems of the conventional method)
The diagnosis result presented by the advice generation system and the route that outputs the diagnosis result are stored in the storage unit 33 without creating a reference table, but there are problems that the listability is lacking and management is difficult. On the other hand, in the reference table method, it becomes clear at a glance what kind of process was used to execute various advice data, diagnosis results, ranking results, comparison results, etc., and what kind of evaluation index was used.

(Operation of table reference method (see FIG. 93))
The usual advice data generation route is as described above. On the other hand, in the inquiry route, a question comes first, and the question is referred to in the information generation table. For example, if a task to calculate the winning percentage is found, the work procedure will be clarified from the table, and if you continue the work until the result is obtained, the winning percentage at the present time will be calculated immediately like the normal route. become. Obviously, even with the same winning percentage of Mr. A, the winning percentage will be different if the dates of release are different. The procedure once learned is automated and recalculated every day, and all the calculation results and processes are stored in the storage unit 33 and can be retrieved at any time.

As shown in FIG. 93, each step from the second step to the eleventh step is automated by this table method. For example, for the issue of wanting the overall profit / loss ratio stock ranking for 2020, we instructed to create trading data to be aggregated for each period in 2020 (extraction condition: period = 2020), and component trading data for each stock. Is created and aggregated for each issue (classification condition: investment target: issue, aggregation rule: for each issue), and the term total profit / loss ratio corresponds to the profit / loss. Select the display method corresponding to these result sets in "Evaluation index = Total profit / loss ratio" and "Operation: = Ranking", and the table reference for all phases is decided. As a result, the trading profit / loss ratio stock ranking in 2020 The result is displayed. Once recorded in the table, once these associations are set in the table, articles and issues are automatically resolved. All of these fourth phases may be automated or partial. And, the creation of these tables also plays an important role in AI learning, which is to train AI.

(Effect of table reference method (Fig. 93))
As the data in the information generation table is added, the number of inquiries that can be referred to increases, and a special effect of solving various investment issues can be expected. Centralized management is difficult because it is not managed in a separate table in the conventional method, but in this method, centralized management is easy, the history can be easily checked, and the past result history can be easily displayed to the user. It becomes. Even with the input method, various issues and articles can be automatically generated by the information processing system, but with the table reference method, it is possible to create AI and capture various needs, so special effects can be expected. In the selection method, the administrator prepares an issue or article, and when the user or administrator selects it on the user terminal, various conditions are determined, the steps from the second step to the eleventh step are taken, and the result is output. Will be done. In the table reference method, the input can be selected by the user or administrator, and if it is an issue or article in the table, proceed from the first phase, and if it does not correspond to the table, there is to create a new rule. A screen for adding a new item in the corresponding table will appear, and if you add it, you can make it like taking the next step. Users and managers can retrieve necessary articles and issues, enhance the table, and can expect special effects such as being able to answer common issues immediately.

(Specific example of table reference method)
Accumulation of data in the regular route: In the regular route, the calculation of evaluation indexes, the calculation of diagnostic results, etc. are managed from the trading data. In addition to the examples given above, for example, when asked what the average rate of return of the winners of Softbank shares is, the trading data to be aggregated by investment target (extraction condition: stock = Softbank). ), Winning profit level Trading data (profit / loss = winning profit rate) is created (evaluation index = average of winning profit rate for each investor), and the operation is the display of the evaluation index. These are familiar to all the concrete examples written so far and are applicable to all the concrete examples described therein.

(Specific example 2 of the table reference method)
Explaining with reference to FIG. 89, for example, when the information processing system is requested to have an issue of what is the average trading profit / loss ratio of all investors of S company stock in 2019, the first issue requested is as follows. The procedure of is instructed to the information processing system. Instructed to create the trading data to be aggregated by period in 2019 with "Extraction condition: Brand code = XXX (S1 company stock)", "Instruction to create trading profit / loss level trading data of the trading data, trading record It is recorded in the table by instructing "calculation of trading profit / loss ratio for each, calculation of average trading profit / loss ratio, and display of this in an appropriate manner". For the next issue, whether it is the investment of S2 company stock in 2020 or the average trading profit / loss ratio of the whole, it is because the structure is the same as in 2020 just by changing the stock code. If the year and brand code are prepared in a separate table, they can be read and referenced in the information processing system, so it can be regarded as an existing issue rather than a new issue.

(Accumulation of data in inquiry route)
As for the inquiry route, the data is recorded in the same table in the same way. If you want a winning percentage every day, the same procedure is executed, but since various data are refreshed every day, the winning percentage also changes. By accumulating such data with the date, it becomes easy to display the transition of the winning percentage. As mentioned earlier, the advice generation process is, on the flip side, an inquiry resolution process. If the history can be referred to immediately and the transition can be graphed, a special effect of clarifying how the problem has been solved can be expected.

FIG. 74 is a diagram showing an AI machine learning process of the information processing process according to the fourth embodiment of the present invention.

(AI learning method (explanation of FIG. 74))
The problem of the above reference table method is that it is necessary to accumulate reference tables, and as the accumulation progresses, various problems can be solved conveniently, but the problem is that the accuracy changes depending on the degree of accumulation of this table. be. On the other hand, in the AI learning method, since the method of creating trading data, the calculation of evaluation indexes, and the relationship of the combination of various results are learned, those relationships are also related to the first advice generation and the first task. Utilizing what we have learned from sexual learning, it is possible to solve problems, generate advice (including diagnosis, etc.), and try to generate articles. The more you use this, the more you can learn the information processing system from various angles by creating such trading data at this time, and you can expect effects that are not in the table. In the reference table method, the administrator or user must manually input the issues and articles that have never existed, and the associations that have never existed, and increase the associations. In the case of the AI method, this association is automated, machine learning is measured, and guessing and verification are repeated so that AI responds to the demands of users and managers to improve the accuracy of the association.

(Problems of the conventional method)
As mentioned earlier, the problems of the table method and the method before it are the problems of the conventional method. The reference table method requires the work of adding things that are not mentioned above, and the notation fluctuations, for example, 2020 to 2020, this year, etc., the user input is various and the same. Various table associations must be prepared to produce results.

(Action of AI method)
The difference from the table method is that there is a learning department, and advice generation data and machine learning for problem solving can be performed. How to get the winning profit rate and how to get the losing loss rate must be calculated from different trading data, but if AI machine learning progresses, the winning profit trading table will be based on the relationship between the profit rate and the loss rate. Then, you will be able to refer to the losing loss trading table. This is a special effect that the table method does not have.

(Effect of AI method)
In addition to the effects mentioned above, various possibilities will be created as machine learning progresses, such as this data for this person, this advice for this person, and this ranking because this person's weakness is here. If it is the AI method, it will be possible to gradually read the match between 2020, 2020, and last year in the previous example, and the learning effect will work and improve so that the demand can be met. The table used in the table method can be used as it is as teacher data, and the learned data is accumulated as it is used, and the more data that can be referred to, the higher the accuracy, and various investment issues and investments. You will be able to respond to the news. Then, the trained data will be very valuable.

(Specific example of AI method)
The specific examples described in each of the above steps are specific examples that can be converted to AI, and all of them apply, and the steps until the conversion to AI is realized are a part of AI conversion from the second step to the eleventh step. However, it may be advanced step by step, or AI may be advanced in all steps (from the first face to the fourth phase). It is a very useful method for the information processing system, which has very complicated and wide-ranging analysis and functions such as investment issues and problem solving, diagnosis and generation of advice data.

In addition to the examples given above, there are the following specific examples.

(Specific example 1)
The number of people who are making trading profits with A brand is increasing. In particular, investors with a high probability of success have begun to purchase, and it is conceivable to present this information to investors who have failed as recommended information.

(Specific example 2)
The number of people who refer to Twitter and fail is increasing, and in the current market price, investors who refer to the quarterly report are overwhelmingly more successful than those who refer to Twitter. For example, AI derives comparative data and displays it in order to convey that fact.

(Specific example 3)
Mr. A's investment results have come here and are far inferior to everyone's average. The cause is shown in this evaluation value, and it is obvious when compared with the average, so it can be fully expected that it will be displayed and comments will be added.

[Appendix 1]
In order to solve the above problems, the information generation device according to one aspect of the present invention is an information generation device that generates information regarding the evaluation of the profit and loss of the investment product, and acquires the trading data of the investment product for a period of time. Profit and loss divided into levels for each period according to the trading status of the above investment products in each period by creating trading data to be aggregated by period that classifies the trading data for each period and using the trading data to be aggregated by period. Create trading profit / loss level trading data that is the source of trading profit / loss, which is one of , To calculate the trading profit / loss level evaluation index for evaluating the trading profit / loss which is one of the leveled profit / loss, and to evaluate the unrealized profit / loss which is one of the leveled profit / loss from the above unrealized profit / loss level trading data. It is equipped with an information generation unit that calculates an unrealized gain / loss level evaluation index and generates evaluation information of trading gain / loss and unrealized gain / loss for each period by using the above-mentioned trading profit / loss level evaluation index and the above-mentioned unrealized gain / loss level evaluation index. ..

According to the above configuration, it is possible to provide an evaluation regarding the total profit and loss of investment products. In addition, by calculating each evaluation index of the trading data subject to aggregation by period, the trading status or holding status of each period is clarified, and the characteristics of investment products in the group for each period are clarified.

In the information generation device according to one aspect of the present invention, when the period is a period from the first time point to the second time point, the information generation unit is the first of the above-mentioned period-specific aggregated trading data. Regarding the trading data of investment products purchased at the time of, the standard evaluation value of the investment product is changed from the unit price at the time of purchase to the unit price at the first time, and the second of the above-mentioned trading data subject to aggregation by period Regarding the trading data of the investment product held at the time of, the latest closing price of the investment product may be changed from the unit price at the time of sale or the current unit price to the unit price at the second time.

According to the above configuration, by changing the standard valuation amount and the latest closing price of the trading data subject to aggregation by period, it is possible to accurately evaluate the profit and loss of the first level to the fourth level for each period.

In the information generation device according to one aspect of the present invention, the information generation unit uses the trading profit / loss level evaluation index and the unrealized profit / loss level evaluation index to rank within the period, thereby performing the ranking within the period. , Trading profit / loss and unrealized profit / loss ranking information may be generated.

According to the above configuration, the ranking within the period can be confirmed from the ranking result of the profit / loss level evaluation index of each profit / loss level. For example, when the investment targets are ranked according to the winning profit margin of the traded data, the stocks having a high winning profit margin and the stocks having a low winning profit margin are clarified, and the stocks having a high winning profit margin can be selected.

The information generation device according to one aspect of the present invention is an information generation device that generates information regarding the evaluation of profit and loss of investment products, acquires trading data of the investment products, and classifies the trading data for each investment target. Create trading data to be aggregated by investment target, and use the trading data to be aggregated by investment target to classify the profit and loss for each investment target according to the trading status of the above investment products included in each investment target. Create trading profit / loss level trading data that is the source of one trading profit / loss and unrealized gain / loss level trading data that is the source of unrealized gain / loss that is one of the leveled profits / losses. The trading profit / loss level evaluation index for evaluating the trading profit / loss, which is one of the divided profits / losses, is calculated, and the unrealized profit / loss for evaluating the unrealized profit / loss, which is one of the leveled profits / losses, from the above unrealized profit / loss level trading data. It is provided with an information generation unit that calculates a level evaluation index and generates evaluation information of trading profit / loss and unrealized profit / loss for each investment target by using the trading profit / loss level evaluation index and the unrealized profit / loss level evaluation index.

According to the above configuration, it is possible to provide an evaluation regarding the total profit and loss of investment products. In addition, by calculating each evaluation index of the trading data to be aggregated by investment target, the trading status or holding status of each investment target will be clarified, and the characteristics of investment products in the group for each investment target will be clarified. Play.

In the information generation device according to one aspect of the present invention, the information generation unit compares the trading profit / loss level evaluation index and the unrealized profit / loss level evaluation index between the investment targets, whereby the trading profit / loss between the investment targets is compared. And information showing the comparison result of unrealized gains and losses may be generated.

[Example of implementation by software]
The terminal 2, the server 3, and the control block of the server 30 (particularly, the control unit 22, the control unit 32, the control unit 302, the advice generation unit 321, and the information generation unit 3021) are integrated into an integrated circuit (IC chip) or the like. It may be realized by a formed logic circuit (hardware) or by software.

In the latter case, the terminal 2 and the server 3 include a computer that executes instructions of a program that is software that realizes each function. The computer includes, for example, one or more processors and a computer-readable recording medium that stores the program. Then, in the computer, the processor reads the program from the recording medium and executes the program, thereby achieving the object of the present invention. As the processor, for example, a CPU (Central Processing Unit) can be used. As the recording medium, a "non-temporary tangible medium", for example, a ROM (Read Only Memory) or the like, a tape, a disk, a card, a semiconductor memory, a programmable logic circuit, or the like can be used. Further, a RAM (Random Access Memory) for expanding the above program may be further provided. Further, the program may be supplied to the computer via any transmission medium (communication network, broadcast wave, etc.) capable of transmitting the program. It should be noted that one aspect of the present invention can also be realized in the form of a data signal embedded in a carrier wave, in which the above program is embodied by electronic transmission.

The present invention is not limited to the above-described embodiments, and various modifications can be made within the scope of the claims, and the embodiments obtained by appropriately combining the technical means disclosed in the different embodiments. Is also included in the technical scope of the present invention.

1 Advice presentation system (information presentation system)
2 Terminal (terminal device)
3, 30 servers (information generator)
4 Network 321 Advice generation unit (information generation unit)
3021 Information generator

Claims (17)

An information generator that generates information regarding the evaluation of profit and loss of investment products by investors.
Obtain the trading data of the above investment products and
Create aggregated trading data by investment target, which classifies the above trading data for each investment target.
Unrealized gains and losses that are the source of unrealized gains and losses, which is one of the gains and losses classified by level for each investment target according to the trading status of the above investment products included in each investment target, using the above-mentioned trading data to be aggregated by investment target. Create level trading data,
From the above unrealized profit / loss level trading data, an evaluation index for evaluating unrealized profit / loss, which is one of the leveled profit / loss, is calculated.
An information generation device including an information generation unit that generates evaluation information of unrealized profit / loss for each investment target using the evaluation index. An information generator that generates information regarding the evaluation of profit and loss of investment products by investors.
Obtain the trading data of the above investment products and
Create aggregated trading data by investment target, which classifies the above trading data for each investment target.
Using the above-mentioned trading data to be aggregated by investment target,
Depending on the trading status of the above investment products included in each investment target,
Create trading profit / loss level trading data that is the source of trading profit / loss, which is one of the profit / loss divided into levels for each investment target.
From the above trading profit / loss level trading data, an evaluation index for evaluating trading profit / loss, which is one of the leveled profit / loss, is calculated.
An information generation device including an information generation unit that generates evaluation information of trading profit / loss for each investment target using the evaluation index. The above information generation unit
The information generator according to claim 1 or 2, wherein as the evaluation index, a technical index value at the time of purchase of the investment target, the time of holding the investment target, or the time of sale of the investment target is calculated. .. The above information generation unit
The information generation according to claim 1 or 2, wherein as the evaluation index, a change in fundamentals at the time of purchase of the investment target, the time of holding the investment target, or the time of sale of the investment target is calculated. Device. The above information generation unit
Identify the investment behavior of other investors at the time of purchase of the investment target, at the time of holding the investment target, at the time of sale of the investment target, or after the sale of the investment target, and relate to the investment target of the other investor. The information generator according to claim 1 or 2, wherein the evaluation index is calculated. The above information generation unit
The evaluation index is characterized by calculating an evaluation index for another investment target at the time of purchase of the investment target, at the time of holding the investment target, at the time of selling the investment target, or after the sale of the investment target. The information generator according to claim 1 or 2. The above information generation unit
As the evaluation index, the investor's past investment behavior at the time of purchase of the investment target, the holding time of the investment target, the sale time of the investment target, or after the sale of the investment target is specified, and the investor The information generator according to claim 1 or 2, wherein an evaluation index relating to a past investment target is calculated. The above information generation unit
The information generation device according to claim 1 or 2, wherein the evaluation index is associated with an evaluation index calculated from the investment products owned by the investor. The above information generation unit
A chart linking the investment target currently held and the trading behavior for the investment target is displayed, and the purchase date of the investment target, the sale date of the investment target, the holding period of the investment target, and the holding period of the investment target are displayed. The information generator according to claim 1 or 2, wherein a chart for displaying an evaluation index that influences investment profit / loss affected by price movements is generated and displayed. The above information generation unit
A claim characterized by calculating an evaluation index for each investor, each period, and each investment target of the subordinate concept of the investment target, and using the calculated evaluation index to generate evaluation information for each investment target. The information generator according to 1 or 2. The information generation device according to claim 1 or 2, wherein the information generation unit generates display information of a chart personalized for each investor based on a trading behavior for an investment target. Claim 1 is characterized in that the information generation unit generates information indicating a comparison result between investors or investment targets by comparing the evaluation indexes between investors or investment targets. The information generator according to any one of items 1 to 11. The above information generation unit
Any of claims 1 to 12, wherein the evaluation index is ranked among investors or investment targets to generate information indicating a ranking result between investors or investment targets. The information generator according to item 1. The above information generation unit
One of claims 1 to 13, characterized in that information indicating the diagnostic result of the investor or the investment target is generated by diagnosing the trading result of the investor or the investment target from the evaluation index. The information generator described in. The above information generation unit
Claim 1 is characterized in that by giving advice based on the trading results of an investor or an investment target from the evaluation index, information showing advice based on the trading results of the investor or the investment target is generated. The information generator according to any one of 13 to 13. The information generator according to any one of claims 1 to 15.
With the terminal device
It is an information presentation system including
The terminal device is an information presentation system characterized by presenting information generated by the information generation unit to a user. An information generation program for operating a computer as the information generation device according to any one of claims 1 to 15, and for operating the computer as the information generation unit.

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