JP6754283B2 - Transaction support device and transaction support method - Google Patents

Description

The present invention relates to a transaction support device and a transaction support method, and specifically, comprehensively and objectively analyzes price interlocking between products without limitation on the type of industry, market, or the passage of time. Regarding the technology that enables it.

For products that are subject to market transactions or bilateral transactions (the selling price fluctuates even during the day), a technology has been proposed that predicts price fluctuations and uses them as reference information for transactions.

As such a technique, for example, in an information providing system that determines and notifies the client system of a customer to be communicated via a communication network by determining and notifying the market fluctuation factor of each brand to be traded, the communication from the client system. A means for accepting the designation of the target issue via the network, a group storage means for storing each issue grouped according to at least one of the industry or the theme, and a predetermined time-series data of the price movement of the transaction target is received from the outside. A means for storing the price movement storage means of the above, a detection means for detecting a fluctuation of a predetermined value or more by comparing a new one of the time series data with the past one at any time, and a factor of the detected fluctuation. A computer or an electronic circuit realizes a factor determining means for determining the factor and a means for notifying the determined factor to the client system, and the factor determining means stores the price movement for each issue in the same market as the target issue. By reading time-series data from the means and calculating the rate of increase / decrease, the existence or nonexistence of market interlocking, which is an event in which the number of issues that have increased / decreased by a predetermined value or more in the same market in the same market becomes the first ratio or more If the market linkage exists, it is determined that the factor of the fluctuation is a market factor, and if the factor is not a market factor, it belongs to the same industry or theme group as the target issue by referring to the group storage means. Existence or non-existence of industry-linked or theme-linked, which is an event in which each issue is specified and among these issues, the issue that has risen or fallen by a predetermined value or more in the same direction as the target issue is at least a predetermined ratio associated with that industry or theme. If there is an industry-linked or theme-linked factor, it is determined that the factor of the fluctuation is an industry factor or a theme factor, and if the factor of the fluctuation is not any of the market factor, the industry factor, or the theme factor, the target is An information providing system (see Patent Document 1), which is characterized in that the factors for the rise and fall of a brand are determined to be factors peculiar to the individual brand, has been proposed.

Japanese Unexamined Patent Publication No. 2004-280810

In the stock market where a large number of stocks are traded, securities analysts and individual investors are constantly analyzing the triggers and factors of stock price fluctuations. However, such an analysis predicts the correlation of stock prices for stocks in a limited range such as by industry or technical field.

In the above-mentioned analysis method, there is a limit to the amount and range of information that can be investigated and examined by humans, and it is possible to freely analyze the correlation of stock prices of stocks in different industries, technical fields or markets. Has not been realized. In addition, under such conditions, it is difficult to timely grasp the transition of correlation factors over time and reflect this in the analysis.

Therefore, an object of the present invention is to provide a technique capable of efficiently and comprehensively and objectively analyzing price linkage between products without limitation on the type of industry, market, or the passage of time.

The transaction support device of the present invention that solves the above problems has a storage device that holds a price prediction formula for each of a plurality of products whose prices can fluctuate, and reads information on the price prediction formula between the products from the storage device. By calculating the relative magnitude of the coefficient of each variable in the price prediction formula indicated by the information, the contribution of each variable to the price determination is specified, and among the combinations of variables in each of the price prediction formulas, the above An operation that identifies a combination in which the total contribution degree is equal to or greater than a predetermined threshold, identifies a product group that matches the combination of the specified variables between the products, and outputs information of the product group to the user terminal. It is characterized by including a device.

Also, trading support method of the present invention relates to an information processing apparatus, a storage device for holding a plurality of items each price prediction expression can price fluctuations, the said price prediction equation information between each of said product By reading from the storage device and calculating the relative magnitude of the coefficient of each variable in the price prediction formula indicated by the information, the contribution of each variable to the price determination is specified, and the variable in each of the price prediction formulas Among the combinations, the combination in which the total contribution degree is equal to or more than a predetermined threshold value is specified, the product group in which the specified combination of the variables matches is specified between the products, and the information of the product group is transmitted to the user terminal. It is characterized by outputting to.

According to the present invention, it is possible to efficiently and comprehensively and objectively analyze the price linkage between products without limitation on the type of industry, the market, or the passage of time.

It is a network configuration diagram including the transaction support device of this embodiment. It is a figure which shows the hardware configuration example of the transaction support apparatus in this embodiment. It is a figure which shows the data structure example of the price prediction formula table of this embodiment. It is a figure which shows the data structure example of the price history table of this embodiment. It is a figure which shows the flow example 1 of the transaction support method in this embodiment. It is a figure which shows the combination concept of the variable (parameter) in this embodiment. It is a figure which shows the screen example 1 in this embodiment. It is a figure which shows the flow example 2 of the transaction support method in this embodiment. It is a figure which shows the screen example 2 in this embodiment. It is a figure which shows the flow example 3 of the transaction support method in this embodiment.

--- Network configuration ---

Embodiments of the present invention will be described in detail below with reference to the drawings. FIG. 1 is a network configuration diagram including the transaction support device 100 of the present embodiment. The transaction support device 100 shown in FIG. 1 is a computer that can efficiently and comprehensively and objectively analyze price interlocking between products without limitation on the type of industry, market, or the passage of time.

The transaction support device 100 of the present embodiment is a device that provides information that can be used as a reference for buying and selling, such as stocks and currencies, regarding products whose selling prices are formed by the existence of sellers and buyers and their actions. However, the information provided here is not the estimation result of the product price itself, but the information of the product group having price linkage. That is, it is information on a group of products including those products by assuming a situation in which the prices of other products that are price-linked to the price fluctuations of a certain product fluctuate in the same manner.

Such a transaction support device 100 can be assumed to be a server device communicably connected to a user terminal 200, a statistical analysis device 300, and an information distribution device 400 via an appropriate network 10 such as the Internet. Specifically, the transaction support device 100 will be operated by an appropriate financial institution such as a securities company or a bank that handles the above-mentioned products, or a business operator that provides information to these financial institutions.

On the other hand, the user terminal 200 is a terminal of a user who receives information from the transaction support device 100.

Further, the statistical analysis device 300 is a device that analyzes information provided by, for example, the information distribution device 400 by an appropriate analysis engine such as a statistical analysis tool or an algorithm of artificial intelligence, and generates a price prediction formula for each product. .. The method of generating such a price prediction formula is not particularly limited in this embodiment, and the existing technology may be appropriately adopted. Further, the statistical analysis device 300 is a device that provides the information of the price prediction formula thus generated to the transaction support device 100 of the present embodiment. The function of the statistical analysis device 300 may be provided in the transaction support device 100.

Further, the information distribution device 400 is a device that distributes various types of information that can be used to generate the above-mentioned price prediction formula to the statistical analysis device 300. Examples of the distribution information include market value information of the stock, information of the issuing company of the stock, various economic indicators, political information, weather information, and the like.
--- Hardware configuration ---

FIG. 2 is a diagram showing a hardware configuration example of the transaction support device 100 according to the present embodiment. The hardware configuration of the transaction support device 100 of this embodiment is as follows.

That is, the transaction support device 100 is held in a storage device 101 composed of an appropriate non-volatile storage element such as an SSD (Solid State Drive) or a hard disk drive, a memory 103 composed of a volatile storage element such as a RAM, and a storage device 101. The program 102 is read into the memory 103 and executed to perform overall control of the device itself, and is connected to a computing device 104 such as a CPU that performs various determinations, calculations and control processes, and a network 10 to perform communication processing with other devices. A communication device 105 is provided.

In the storage device 101, in addition to the program 102 for implementing the function required as the transaction support device of the present embodiment, the threshold value 110 used for determining the similarity between the price prediction formulas, the price prediction formula table 125, And, at least the price history table 126 is stored. The threshold 110, the price prediction table 125, and the price history table 126 will be described later.
--- Data structure example ---

Subsequently, the tables used by the transaction support device 100 of the present embodiment will be described. FIG. 3 shows an example of the price forecast formula table 125 in this embodiment.

The price prediction formula table 125 of the present embodiment is a table that stores the price prediction formula for each product. The data structure is a collection of records associated with a price forecast formula for each period of the product, using the product ID that uniquely identifies the product as a key. This price prediction formula is distributed from the above-mentioned statistical analysis device 300 and stored in the price prediction formula table 125.

The price forecast formula for each period is a formula for predicting the price of the corresponding product at the relevant period (for example, period A: November 1, 2016).

Further, FIG. 4 shows an example of the price history table 126 in this embodiment. The price history table 126 of the present embodiment is a table that stores information on the actual price of each product at each time period.

The data structure is a collection of records associated with price data files for each period of the product, using the product ID that uniquely identifies the product as a key. This price data file contains data showing price movements (eg, a chart of product prices from the start time of trading to the end time of trading in the market) at the relevant time (for example, time x: October 1, 2016) of the corresponding product. This is the stored file.
--- Flow example 1 ---

Hereinafter, the actual procedure of the transaction support method in the present embodiment will be described with reference to the figure. Various operations corresponding to the transaction support method described below are realized by a program read by the transaction support device 100 into a memory or the like and executed. This program is composed of codes for performing various operations described below.

FIG. 5 is a diagram showing a flow example 1 of the transaction support method in the present embodiment. First, the transaction support device 100 reads the price prediction formula information regarding the predetermined time of each product from the price prediction formula table 125 of the storage device 101 (s100). Here, the predetermined time is a time designated in advance from the user terminal 200, or simply the latest time.

Here, as an example for explanation, it is assumed that the following price forecast formulas for products A to C are read.

-Price prediction formula for product A = variable 1 x 32 + variable 2 x 10 + variable 3 x 8 + 10

-Price prediction formula for product B = variable 1 x 22-variable 3 x 10 + variable 4 x 8 + 5

-Price prediction formula for product C = variable 1 x 3 + variable 2 x 20-variable 5 x 45 + 7

Next, the transaction support device 100 specifies the degree of contribution of each variable (parameter) in the price prediction formula to the price determination for each product, that is, each price prediction formula read for the goods A to C in the above-mentioned s100. (S101).

For example, for each price forecast formula, the relative magnitude of the coefficient of each variable in the price forecast formula is calculated, and this is used as the degree of contribution. Regarding the price prediction formula of product A in the above example, the total value of the coefficients of all the variables (variable 1, variable 2, variable 3) included in the price prediction formula is calculated as 32 + 10 + 8 = 50, and this total. By dividing the coefficient of each variable by the value, the contribution of variable 1 is 64% (= 32/50), the contribution of variable 2 is 20% (= 10/50), and the contribution of variable 3 is 16. It can be calculated as% (= 8/50), etc. Similarly, regarding the price prediction formula for product B, the contribution of variable 1 is 55% (= 22/40), the contribution of variable 3 is 25% (= 10/40), and the contribution of variable 4 is 20%. (= 8/40) Also, regarding the price prediction formula of the product C, the contribution of the variable 1 is 4% (= 3/68), the contribution of the variable 2 is 30% (= 20/68), and the variable 5 Is calculated as 66% (= 45/68), etc.

Further, the transaction support device 100 identifies, based on the contribution calculated as described above, the combination of variables in each of the price prediction formulas read in s100, in which the total contribution is equal to or greater than the threshold value (s102). .. The threshold value used here is a threshold value 110 that the transaction support device 100 holds in advance in the storage device 101. Specifically, the value is "80%".

A specific example of the combination of variables is shown in FIG. As shown in the example of FIG. 6, in each of the products A, B, and C, the combination of variables in which the total contribution (price determinant) exceeds 80% of the threshold value is in the product A.

Combination of variable 1 and variable 2, combination of variable 1 and variable 3, combination of variable 1 and variable 2 and variable 3, combination of variable 1 and variable 3 in product B, combination of variable 1 and variable 3 and variable 4, product In C, it is a combination of variable 2 and variable 5, and a combination of variable 1, variable 2 and variable 5.

Subsequently, the transaction support device 100 collates the combination of variables in the price prediction formula specified as described above among the products, and identifies the product group in which the combination of variables matches (s103). In the case of the above example, since the combination of the variable 1 and the variable 3 of the product A and the product B match, respectively, it is specified that there is a similarity in the price determination, and the product group is configured. On the other hand, in the product A and the product C, there is nothing in common between the combinations of the respective variables, and it is specified that there is no similarity in the price determination, and the product group is not formed. Similarly, in the products B and C, there is nothing in common between the combinations of the respective variables, and it is specified that there is no similarity in the pricing, and the product group is not formed.

Next, the transaction support device 100 transmits the information of the specified product group to a predetermined device such as the user terminal 200 (s104), and ends the process. Here, FIG. 7 shows an example of a screen 700 of product group information transmitted and displayed by the transaction support device 100 to the user terminal 200. As illustrated in FIG. 7, the screen 700 includes a message indicating that the price linkage at the time A is recognized for the product A and the product B constituting the product group.

A user who browses such a message on the user terminal 200 confirms, for example, the current price movements of product A and product B, and the price of one product has risen from the start of trading, but the price of the other product has started trading. If it has not risen since time, it is possible to take measures such as placing a buy order for the other product in anticipation of a price increase for the other product.

As described above, the information provided by the transaction support device 100 can be identified regardless of the type of industry or the market in which the transaction is traded, and the price is more comprehensive than the conventional analysis by securities analysts and investors. It is possible to estimate a stock group that is expected to be linked, that is, a product group.
--- Flow example 2 ---

Next, unlike the above-mentioned flow example 1, the processing performed for one product will be described with reference to the figure. FIG. 8 is a diagram showing a flow example 2 of the transaction support method in the present embodiment.

In this case, the transaction support device 100 reads the price prediction formula information for each of the different times from the price prediction formula table 125 of the storage device 101 for a certain product (s200). Here, one product is a product designated in advance from the user terminal 200.

Here, as an example for explanation, it is assumed that the following price forecast formulas for each of the periods x to z of the product A are read.

・ Price forecast formula for time x = variable 1 × 32 + variable 2 × 10 + variable 3 × 8 + 10

・ Price forecast formula for time y = variable 1 × 22-variable 3 × 10 + variable 4 × 8 + 5

-Price forecast formula for time z = variable 1 x 3 + variable 2 x 20-variable 5 x 45 + 7

Next, the transaction support device 100 compares the price prediction formulas of the product A read for each of the periods x, y, and z in the above-mentioned s200 for each period, and determines the similarity (s201). This similarity determination method specifies the combination of variables in the price prediction formula for each period, as in the flow example 1 described above.

Subsequently, the transaction support device 100 collates the combination of variables in the price prediction formula specified as described above between the periods x, y, and z, and identifies the period group in which the combination of variables matches (s202). .. In the case of the above example, since the combinations of the variable 1 and the variable 3 are the same for the time x and the time y, respectively, it is specified that there is a similarity in the price determination, and the time group is formed.

Next, the transaction support device 100 reads information on price movements related to the product A in the past period of the specified period group (in the case of the above example, period x, period y) from the price history table 126, and reads this from the price history table 126. It is transmitted to the terminal 200 (s203), and the process ends.

Here, FIG. 9 shows an example of the screen 900 of the price movement information of the product A transmitted and displayed by the transaction support device 100 to the user terminal 200. As illustrated in FIG. 9, the screen 900 is a file showing the possibility that the price movements are similar for the time x and the time y that constitute the time group for the product A, and the price movement in the time y, which is the past time. And will be shown.
--- Flow example 3 ---

Next, the above-mentioned update process of the threshold value 110 will be described with reference to the figure. FIG. 10 is a diagram showing a flow example 3 of the transaction support method in the present embodiment.

In this case, the transaction support device 100 acquires the price movement information of each product constituting the corresponding product group from the price history table 126 after specifying the product group in s103 of the above-mentioned flow example 1 (s300). In this case, it is assumed that the transaction support device 100 acquires the latest price information of each product from the information distribution device 400 at regular time intervals and stores it in the price history table 126.

Next, the transaction support device 100 collates the price movement information of each of the corresponding products after the above-mentioned identification of the product group, and determines the degree of price interlocking between the products (s301).

In this case, the transaction support device 100 increases or decreases the price of each product in the corresponding time zone, for example, based on the product price per minute in the time zone from the date and time α when the product group is specified to the date and time β 10 minutes later. Calculate the rate. In this calculation, a regression line is obtained by performing regression analysis with each time of each minute in the above-mentioned time zone and the product price at the corresponding time as variables, and the slope of this regression line is used as the price increase / decrease rate. .. For example, if the slope of the regression line obtained for the product A that constitutes the product group is +5, the price increase / decrease rate in the corresponding time zone is + 5%, and the slope of the regression line obtained for the product B that also constitutes the product group is-. If it is 2, the price increase / decrease rate in the corresponding time zone is set to -2% or the like.

Further, the transaction support device 100 compares the price increase / decrease rates obtained as described above among the products, and determines to what extent the trends of price movements among the products match, that is, the degree of price linkage. To do. At this time, the transaction support device 100 first determines whether the positive / negative of the price increase / decrease rate is different between the products, and if the positive / negative is different, it is determined that there is no price linkage. Further, when the positive and negative of the price increase / decrease rate match between the products, the transaction support device 100 further determines whether the difference in the absolute value is within a predetermined reference (eg, within 2%). If the difference in the absolute value of the price increase / decrease rate is within a predetermined standard in this determination, it is determined that the price linkage is sufficient. Further, if the difference in the absolute value of the price increase / decrease rate exceeds a predetermined standard in this determination, it is determined that the price is linked, but the degree is low.

As a result of the determination as described above, the transaction support device 100 determines that the positive and negative of the price increase / decrease rate match between the corresponding products (s302: y), and the difference between the absolute values is within the standard (s303: y). That is, since there is sufficient price linkage between the corresponding products and it is not necessary to update the threshold value 110, the process is terminated.

On the other hand, in the transaction support device 100, as a result of the determination as described above, the positive and negative of the price increase / decrease rate match between the corresponding products (s302: y), but the difference in the absolute value exceeds the standard. (S303: n) Since the price linkage between the corresponding products is insufficient, the threshold 110 is increased by, for example, 10%, that is, an update is performed to identify the product group according to a strict standard (s304). .. In the above example, "80%", which is the value of the threshold value 110, is set to "90%".

Further, when the transaction support device 100 determines that the positive / negative of the price increase / decrease rate does not match between the corresponding products as a result of the determination as described above (s302: n), there is no price linkage between the corresponding products. Therefore, an update that gradually increases the threshold value 110, for example, is executed (s305). In the above example, "80%", which is the value of the threshold value 110, is set to "90%".

Although the best mode for carrying out the present invention has been specifically described above, the present invention is not limited to this, and various modifications can be made without departing from the gist thereof.

According to this embodiment, it is possible to efficiently and comprehensively and objectively analyze the price linkage between products without limitation on the type of industry, the market, or the passage of time.

The description herein reveals at least the following: That is, in the transaction support device of the present embodiment, the arithmetic unit specifies the degree of contribution of each parameter in the price prediction formula to the price determination in the determination, and the combination of parameters in each of the price prediction formulas is described. A combination in which the total contribution degree is equal to or higher than a predetermined threshold value is specified, a product group in which the specified combination matches is specified for each of the products, and information of the product group is output to a predetermined device. May be.

According to this, it is possible to accurately identify a product group that matches the factors that mainly drive price formation, that is, a product group whose price fluctuates due to the same factor.

Further, in the transaction support device of the present embodiment, the storage device holds a price prediction formula for each of the products at different predetermined times, and the arithmetic unit holds the price prediction formula of the predetermined product at the time of the determination. When the similarity of the price prediction formulas is determined by a predetermined algorithm between the different predetermined times and the price prediction formulas show a predetermined similarity by the determination, the predetermined time in the past of the different predetermined times It may be said that predetermined information about a product is output to a predetermined device.

According to this, not only between different products, but also for a specific product, for example, a past price forecast formula in which the most recent price forecast formula and the main factor of price formation are similar is specified, and the price movement of the corresponding product in this past period is specified. Information can be provided to investors, etc. as reference information on price movements of the relevant products during the next investment period.

Further, in the transaction support device of the present embodiment, the arithmetic unit is used to specify the combination according to the content of price interlocking between the products constituting the product group after the product group is specified. The process of updating the threshold value by a predetermined algorithm may be further executed.

According to this, for the product group specified by the above-mentioned judgment or the like, the price interlocking between the corresponding products is verified by the actual price movement, and as a result, when the price interlocking falls below a predetermined level, the above-mentioned threshold value is obtained. Standard maintenance such as increasing the value of is increased by a predetermined ratio becomes possible.

In the transaction support method of the present embodiment, the information processing apparatus specifies the degree of contribution of each parameter in the price prediction formula to the price determination in the determination, and the contribution of the combination of parameters in each of the price prediction formulas. A combination in which the total price is equal to or greater than a predetermined threshold value may be specified, a product group matching the specified combination may be specified for each of the products, and information on the product group may be output to a predetermined device.

In the transaction support method of the present embodiment, the information processing device holds a price prediction formula for each of the products at different predetermined times in the storage device, and at the time of the determination, the different predetermined time of the predetermined product. When the similarity of the price prediction formulas is determined by a predetermined algorithm and the price prediction formulas show a predetermined similarity by the determination, the predetermined information regarding the predetermined product in the past time among the different predetermined times. May be output to a predetermined device.

In the transaction support method of the present embodiment, the threshold value used by the information processing device to specify the combination according to the content of price interlocking between the products constituting the product group after the product group is specified. May be further executed by the process of updating with a predetermined algorithm.

10 Network 100 Transaction support device 101 Storage device 102 Program 103 Memory 104 Arithmetic device 105 Communication device 110 Threshold 125 Price prediction formula table 126 Price history table 200 User terminal 300 Statistical analysis device 400 Information distribution device

Claims (6)

A storage device that holds the price forecast formula for each of multiple products whose prices can fluctuate,
The information of the price prediction formula is read from the storage device for each of the products, and the relative magnitude of the coefficient of each variable in the price prediction formula indicated by the information is calculated to determine the price of each variable. The degree of contribution is specified, and among the combinations of variables in each of the price prediction formulas, the combination in which the total of the degree of contribution is equal to or greater than a predetermined threshold is specified, and the combination of the specified variables matches between the products. An arithmetic device that identifies a product group and outputs information about the product group to a user terminal .
A transaction support device characterized by being equipped with. The storage device is
It holds the price forecast formula for each of the products at different predetermined times and the price information for each of the products at each time .
The arithmetic unit
The contribution of each variable in the price prediction formula is specified for the different predetermined time of the predetermined product, and the total of the contributions of the combinations of variables in each of the different price prediction formulas at the different predetermined time is equal to or more than the predetermined threshold. identify combination is, for between the different predetermined times, to identify when a group of combinations of the identified said variable matches the predetermined product price movement information on the timing of past of the timing group, wherein It is read from the price information of the storage device and output to the user terminal .
The transaction support device according to claim 1. The arithmetic unit
Information on the latest price of each of the products is acquired from the information distribution device at regular intervals, and the information is stored in the storage device.
Based on the latest price information of each product in the product group in a predetermined time zone after the identification of the product group, the price increase / decrease rate of each product in the time zone is calculated, and the calculated price increase / decrease rate is calculated. Is collated among the products of the product group, and when the difference in the price increase / decrease rate between the products exceeds a predetermined standard, a process of further increasing the predetermined threshold used for specifying the combination by a predetermined ratio is further executed. To do,
The transaction support device according to claim 1. The information processing device
Equipped with a storage device that holds the price forecast formula for each of multiple products whose prices can fluctuate.
The information of the price prediction formula is read from the storage device for each of the products, and the relative magnitude of the coefficient of each variable in the price prediction formula indicated by the information is calculated to determine the price of each variable. The degree of contribution is specified, and among the combinations of variables in each of the price prediction formulas, the combination in which the total of the degree of contribution is equal to or greater than a predetermined threshold is specified, and the combination of the specified variables matches between the products. Identify the product group and output the information of the product group to the user terminal .
A transaction support method characterized by that. The information processing device is
In the storage device, the price prediction formula for each of the products at different predetermined times and the price information for each time of the products are held.
The contribution of each variable in the price prediction formula is specified for the different predetermined time of the predetermined product, and the total of the contributions of the combinations of variables in each of the different price prediction formulas at the different predetermined time is equal to or more than the predetermined threshold. identify combination is, for between the different predetermined times, to identify when a group of combinations of the identified said variable matches the predetermined product price movement information on the timing of past of the timing group, wherein Read from the price information of the storage device and output to the user terminal .
The transaction support method according to claim 4, characterized in that. The information processing device is
Information on the latest price of each of the products is acquired from the information distribution device at regular intervals, and the information is stored in the storage device.
Based on the latest price information of each product in the product group in a predetermined time zone after the identification of the product group, the price increase / decrease rate of each product in the time zone is calculated, and the calculated price increase / decrease rate is calculated. Is collated among the products of the product group, and when the difference in the price increase / decrease rate between the products exceeds a predetermined standard, a process of further increasing the predetermined threshold used for specifying the combination by a predetermined ratio is further executed. To do,
The transaction support method according to claim 4, characterized in that.

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