WO2007088700A1 - Economic data processing system - Google Patents

Abstract

An economic data processing system is provided to more flexibly compare waveform data with time-series disposing economic data. A computer instruction processing component group is comprised of a waveform input component (121) for inputting waveform data as a set of time-series values, an equal condition component (124) for storing an equal condition in which time-series disposing economic data are regarded as equivalents to the waveform data, and a comparison-matching processing component (125) for judging whether the economic data are regarded as equivalents to the waveform data, wherein the comparison-matching processing component (125) regards the economic data as equivalents to the waveform data if a relation between values not less than either one of the waveform data and those not less than either one of the economic data is satisfied with an equivalent condition.

Description

 Specification

 Economic data processing system

 Technical field

 The present invention relates to a system and method for processing economic data, and to a system and method for analyzing investment targets, financial information, and financial statements of an enterprise.

 [0002] The present invention also relates to a commodity sales simulation system and a commodity trading simulation method that perform simulation of commodity transactions and output trading results.

The present invention also relates to a commodity trading system and a commodity trading method that actually execute commodity trading.

 Background art

 [0004] In order for an investor to select the most suitable investment from among a large number of investment targets and to make an investment at an optimal timing, it requires an effort to analyze a great deal of information. In many cases, the analysis of economic data is that value information such as price, volume, operating profit margin, profit per share, dividend yield, items of financial statement, and other similar industry or past The value of interest-bearing debt, the amount of sales, and other possible values of relevancy, etc. are comprehensively evaluated by comparing with another value or considering the value itself. In addition, when analyzing how to increase or decrease the value, compare and examine the value of the increase or decrease rate such as 120% compared to the previous year, or plot the value continuously on a graph or chart and see it visually Based on the impression, it was necessary to analyze more comprehensively by recognizing the feature of change.

[0005] As a system for reducing the effort to analyze such a large amount of information, for example, the dividend yield is 2% or more, the equity ratio is 80% or more, and the change rate of ordinary income from last year is There is a mechanism to search for stocks that satisfy the condition that the value is within a certain range, such as 20% or more, and the sales for this term being larger than the average sales for the past 5 years. However, in order to recognize in detail how to change the value, such as the recent price fluctuation, the change in the equity ratio, the change in the ordinary income, and the sales, a graph in which the value is plotted And look at the chart It is necessary to confirm.

 Also, for example, as a method for recognizing the characteristics of waveform data, a calculated value called a moving average or a technical index is known. For example, in the case of obtaining a moving average every 10 periods in price data such as the graph shown in FIG. 12 (a), the first moving average is as shown in FIG. 12 (b) It is obtained by averaging 10 values of. Let this be the K point. Then, by comparing the current value (average value) K obtained by processing the waveform data with the current price data J, it is possible to grasp the features of the waveform data and specify trading conditions. However, in the moving average and other technical indicators, even if they have the same value, the shape of the original waveform data may actually differ as shown in FIG. Thus, for example, a combination of conditions of multiple averages and technical indicators, as shown in Fig. 12 (c), finally the averages plotted on the time axis of the current value can be viewed visually. It is necessary to judge. The same is true if you plot the current value to the past or future position, or plot the past value to the current or future position.

 Also, for example, a method such as a candlestick is known as a method of constructing a first-order chart representing the feature of waveform data. Candlesticks treat the attributes of opening price, high price, low price, and closing price as features, and it is possible to visually grasp the features of waveform data. However, the relationship between the high price and the low price, and where and how much fluctuation occurred, how many times and how it happened, other than the opening price, the high price, the low price, and the value of the closing price on the price axis Information can not be handled. For example, the white candle shown in Fig. 14 (a) is obtained from completely different waveform data as shown in Fig. 14 (b) to (d). As described above, in the candlestick and other chart graphs as well as the moving average, the shape of the original waveform data may actually differ even with the same expression, and the time-series fluctuation of data is illustrated. It is necessary to visually check the resulting chart and carry out comprehensive analysis.

[0008] Also, for example, for describing the meaning or structure of a document or data, which is called XML (extensible schema) in recent years. An XB RL (extensible message reporting language) is created to process a company's financial statements and accounting information electronically and uniformly using a computer using a markup language. In the future, the value of economic data will increase more than ever, and the importance of systems that process a large amount of economic data is considered to increase.

 Among these, time-series data is classified into waveforms by comparing the magnitude of values such as moving average values with different periods, current values, values of technical indicators, etc., and the charts are classified. Thus, there is a technology that makes it easy to view charts by reducing the effort of viewing a large number of charts or defining unique color coding etc. (see, for example, Patent Document 1).

 [0010] In addition, by devising a visual display method, a device has been proposed that allows investors to visually grasp the individual market conditions and the entire market situation at the same time (see Patent Document 2).

 [0011] Also, based on information on price, information on time, order history, and information on trade history, it is possible to automatically specify the type of order, such as order price, order time, limit market, etc. A system for making sales orders has been proposed (see Patent Document 3).

 In addition, the trading transaction simulation apparatus supports the investor by determining the timing of trading based on the value of the divergence from the moving average and displaying a mark representing the timing of trading in a glance. Proposed (see Patent Document 4)

[0013] Further, there has been proposed an apparatus for automatically processing trading orders by receiving trading conditions (see Patent Document 5).

[0014] Also, an apparatus has been proposed that notifies the user of the result of selecting a brand by attribute of the brand, technical analysis and fundamental analysis, and further supports brand selection and decision of trading timing by trading simulation. (See Patent Document 6).

[0015] Also, using a computer, automatically through a data communication network A system for processing trading orders has been proposed (see Patent Document 7). Patent Document 1: Japanese Patent Application Laid-Open No. 2 0 0 3 _ 8 5 3 8 1

 Patent Document 2: Japanese Patent Application Laid-Open No. 2 0 0 3 _ 1 3 2 2 1 4

 Patent Document 3: Japanese Patent Application Laid-Open No. 2 0 0 4 _ 5 4 6 4 3

 Patent Document 4: Japanese Patent Application Laid-Open No. 2 0 0 4 _ 1 1 8 6 9 7

 Patent Document 5: Japanese Patent Application Laid-Open No. 2 0 0 1 _ 1 5 5 0 8 6

 Patent Document 6: Japanese Patent Application Laid-Open No. 2 00 2 _ 2 4 5 4 7

 Patent Document 7: Special Table 2 0 0 2 3 5 4 3 4 8 1

 Disclosure of the invention

 Problem that invention tries to solve

However, in the related art such as Patent Document 2, if different classification conditions are not associated in advance for each waveform pattern, time-series data can not be classified into the waveform pattern, and thus it is determined in advance. There is a problem that it is only possible to classify time series data as waveform patterns.

Furthermore, even with the same waveform pattern, there is a problem that time-series data can be classified only by a predetermined pattern classification algorithm because the classification condition to be associated differs depending on the pattern classification algorithm.

The present invention has been made to solve the above-mentioned problems, and an economic data processing system capable of comparing waveform data with economic data arranged in time series more flexibly than ever. Intended to provide.

 Means to solve the problem

In the economic data processing system of the present invention, waveform input means for inputting waveform data as a set of time series values, and equivalent conditions for considering economic data arranged in time series as equivalent to the waveform data are considered. Equal condition storage means for storing, and equivalent judgment means for judging whether or not the economic data is regarded as equivalent to the waveform data, wherein the equivalence judgment means is any one of the waveform data. If the relationship between one or more values and any one or more of the economic data satisfies the equivalent condition, the economic data is regarded as equivalent to the waveform data. The economic data processing system according to the present invention further comprises error range input means for inputting tolerance error which is a level regarded as equivalent, and the equivalent condition storage means is associated with each of a plurality of the tolerances. It is preferable that each of the stored equivalent conditions be stored, and that the equivalent determination unit make the determination using the equivalent condition associated with the tolerance error input by the error range input unit.

 Further, in the level of the tolerance error of the economic data processing system of the present invention, the level which regards all the economic data as equal to the waveform data, and all the economic data as equal to the waveform data. It is preferable that there is a level not considered and a level provided stepwise between the levels.

 Preferably, the equivalence judging means of the economic data processing system of the present invention makes the judgment again every time the tolerance is changed by the error range inputting means.

 Further, the economic data processing system according to the present invention comprises statistical means for taking statistics on the number of the economic data that the equivalence judging means deems equal to the waveform data, and the equivalence condition The storage means, the statistics corresponding to the tolerance may be the statistics such that the distribution for each level of the number of the economic data that the equivalence judging means considers to be equivalent to the waveform data is a predetermined distribution. It is preferable to make changes based on the statistics taken by the instrument.

 The economic data processing system according to the present invention further comprises data conversion means for adjusting the waveform data and the economic data to a common scale by converting at least one of the waveform data and the economic data. It is preferable that the equivalence judging means make the judgment using the waveform data and the economic data adjusted to the common scale by the data converting means.

Further, in the economic data processing system according to the present invention, the data conversion means matches the common scale by replacing the waveform data and the economic data with character strings according to a predetermined rule, respectively, The judging means It is preferable that the determination as to whether the relationship between the character string in which the value of the data is replaced and the character string in which the value of the economic data is replaced satisfies the equality condition is made by character search.

 Furthermore, in the economic data processing system of the present invention, in the case where the waveform data and the economic data are price data of different currency units, at least one of the waveform data and the economic data is used. It is preferable to convert the waveform data and the economic data into a common unit of price data by converting.

 Preferably, the waveform input means of the economic data processing system of the present invention inputs, as the waveform data, data corresponding to a waveform within a specified range of the waveforms displayed on the screen.

 Further, the economic data of the economic data processing system of the present invention is price fluctuation data of a commodity brand whose transaction price fluctuates, and the economic data processing system is a result of hypothetical trading of the commodity brand. It is preferable that, as a system for simulating, that the price determining means considers the price fluctuation data to be equivalent to the waveform data as a trigger for the transaction.

 Also, the economic data processing system according to the present invention is a statistical storage for taking predetermined statistics from the economic data with respect to data of a predetermined period among the economic data and storing the statistical values in advance before the start of the simulation. The economic data processing system displays the statistical value stored by the statistical storage means with respect to the data of the predetermined period as a simulation result when the data of the predetermined period is the waveform data. It is preferable to do.

 [0030] Further, the economic data of the economic data processing system of the present invention is price fluctuation data of commodity brand whose transaction price fluctuates, and the economic data processing system automatically trades the commodity brand. In the system, it is preferable to use the fact that the price judgment data has regarded the price fluctuation data as being equal to the waveform data as a trigger for the transaction.

[0031] Further, the economic data processing system of the present invention is characterized in that: In the case of a system for simulating the results, it is preferable to take over the waveform data used in the simulation to the automatic transaction.

 Further, the waveform input means of the economic data processing system of the present invention comprises: buy waveform data for specifying a timing at which the commodity brand is bought; sale waveform data for specifying a timing at which the commodity brand is sold; As the waveform data, and the economic data processing system determines that the price variation data is regarded as equivalent to the buying waveform data as a contract to buy the commodity brand, and the price determining device determines the price data as the contract data. It is preferable that, as an opportunity to sell the commodity brand, that the price fluctuation data be regarded as equivalent to the sale waveform data.

 Further, according to the economic data processing system of the present invention, equivalent waveform grouping means for classifying the economic data considered to be equivalent to each other by the equivalence judging means into the same group, and the economic data as icons. Therefore, it is preferable to include display means for displaying in the display area, and association means for associating the appearance and the display position of the icon with each group.

 Preferably, the association means of the economic data processing system according to the present invention associates the appearance and display position of the icon with the attribute of the economic data in addition to the group.

 Further, it is preferable that the association means of the economic data processing system according to the present invention determines the relative appearance and relative position of the icons according to a predetermined condition.

 Further, preferably, the association means of the economic data processing system according to the present invention determines the icon at an absolute position in the display area with a predetermined appearance under a predetermined condition.

 Preferably, the display means of the economic data processing system of the present invention continuously updates the display.

Further, in the economic data processing system of the present invention, the display means may display the icon of economic data closest to a predetermined condition among a plurality of the economic data at a predetermined position of the display area. preferable. In the economic data processing program according to the present invention, waveform input means for inputting waveform data as a set of time series values, and equivalent conditions for considering economic data arranged in time series as equivalent to the waveform data. A computer functioning as an equivalent judgment means for judging whether the economic data is regarded as equivalent to the waveform data, and the equivalence judgment means is any of the waveform data. If the relationship between one or more values and any one or more of the economic data satisfies the equality condition, the economic data is regarded as equivalent to the waveform data.

 Effect of the invention

 According to the present invention, it is possible to provide an economic data processing system that can flexibly compare waveform data with economic data arranged in time series.

 Brief description of the drawings

 FIG. 1 is a block diagram of computer instruction processing components of the present invention.

 [FIG. 2] FIG. 2 is a diagram showing an example of an arbitrary waveform input to the computer instruction processing component group shown in FIG.

 [FIG. 3] FIG. 3 is a diagram for explaining analysis of time-series economic data input to the computer instruction processing component group shown in FIG.

 [FIG. 4] FIG. 4 is a schematic view showing an example of a tolerance range used by the computer instruction processing component group shown in FIG.

 [FIG. 5] FIG. 5 is a block diagram of a network in which the computer instruction processing components shown in FIG. 1 are implemented.

 6 is a block diagram of a computer terminal on which the computer instruction processing components shown in FIG. 1 are implemented.

 [FIG. 7] FIG. 7 is a block diagram showing an example in which the computer instruction processing components shown in FIG. 1 are implemented in the network shown in FIG.

[FIG. 8] FIG. 8 shows the computer instruction processing components shown in FIG. 1 in FIG. FIG. 7 is a block diagram showing an example implemented in a smart network.

 [FIG. 9] FIG. 9 is a block diagram showing a retrieval system of time series economic data by the computer instruction processing component group shown in FIG.

 [FIG. 10] FIG. 10 is a schematic view showing an example of a waveform used by the user as the timing of trading in the computer instruction processing component group shown in FIG.

 [FIG. 11] FIG. 11 is an image diagram showing an economic data display system implemented by a waveform grouping component equivalent to the computer instruction processing component group shown in FIG.

 [FIG. 12] FIG. 12 is a diagram for explaining a conventional moving average.

 [FIG. 13] FIG. 13 is a diagram for explaining a conventional moving average.

 [FIG. 14] FIG. 14 is a diagram for explaining a conventional candlestick.

 Explanation of sign

 [0042] 1 2 1 waveform input component (waveform input means)

 1 2 2 Abstract space arrangement components (data conversion means, statistical means)

 1 2 3 Error range input component 誤差 (Error range input means)

 1 2 4 equivalent condition component (equivalent condition storage means)

 1 2 5 Comparison matching processing component (equity judgment means)

 BEST MODE FOR CARRYING OUT THE INVENTION

The present invention is based on a technology for searching economic data (hereinafter referred to as “time-series economic data”) arranged in time series, and firstly, the configuration of the core economic data processing system I will explain and then explain the configuration using the core system.

 The present system is provided with an apparatus for searching time-series economic data, which may use a set of time-series values as a search query. In addition, this device may have a device for inputting an error range at the time of search. FIG. 1 is a schematic representation of computer instruction processing components in which systems and methods may be implemented in accordance with the principles of the present invention.

[0045] ♦ Input ♦ The input from the waveform input component 1 2 1 as waveform input means and the input from the error range input component 1 2 3 as error range input means are input terminals such as a keyboard and a mouse to use the system user May enter data, data of the economic data distribution service may be entered without the user, or it may be input from another component for obtaining economic data, main memory, ROM It may be input from a computer storage device such as a hard disk or disk device.

The input from the waveform input component 12 1 may be waveform data of a different coordinate system, or data of the same coordinate system. A coordinate system is relative information on the position and value of each point in time series information. For example, while the user is looking at a computer monitor etc., it is an input device such as a keyboard or mouse. When inputting an arbitrary waveform such as), the coordinate system is, for example, the upper left of the computer monitor or the drawing area of the waveform as the origin (0, 0) as shown in Fig. 2 (b). It may be expressed as a combination of the distance from the left end and the distance from the top end as (1 1 0, 2 3 0). Also, for example, coordinates of each point of time-series economic data may be input by specifying a range of time-series data represented by a bar graph, a line graph, or a candlestick as shown in FIG. 2 (c). You may enter time-series economic data such as prices as shown in Figure 2 (d). Also, for time-series economic data, data may be input at regular intervals, such as daily, monthly, or yearly intervals, and the time interval may not be constant.

 [0047] ♦ Abstract space arrangement String ♦

 Waveform Input Component 1 Economic time-series waveform data (set of time-series values) input from 1 2 1 can be compared and analyzed even with time-series data in different coordinate systems. Abstract space arrangement component 1 2 2 as a transformation means is arranged in an abstract space (common measure).

That is, the input waveform data is data of different coordinate systems, such as the actual price fluctuation data having price and time information and the coordinate of the mouse pointer on a computer generally having the upper left as the origin. Which may be the same In order to compare and determine in one coordinate system, transform to a common coordinate system.

 For example, assuming that the horizontal length of the input area of the free input device is variable WIDTH, the vertical length is variable HE I GHT, and the position of the mouse pointer whose origin is the upper left is (X, Y). The conversion value to the coordinate system (abstract space) whose origin is at the lower left is represented by (X, HEIGHT-Y).

 The transformation method of the coordinate system and the construction method of the abstract space are not limited to this. For example, an abstract space may be configured based on the ratio of unevenness of input waveform data, or an abstract space may be configured based on the characteristics of line segments connecting arbitrary points of waveform data such as inclination and length. It may be configured. Also, for example, when price data of different currency units such as yen and dollar are arranged in an abstract space, the dollar may be calculated and arranged in yen conversion, or the yen may be calculated and arranged in dollar conversion. You may define an abstract unit that can represent all currency units, and convert and arrange time series economic data of all currencies into the predetermined abstract unit.

 [0051] Next, analysis techniques for arranging time-series economic data in an abstract space will be described.

 The size of the horizontal axis of the waveform shown in FIG. 3 (a) is W, and the size of the vertical axis of the waveform is H. Each value of the horizontal axis of each point P 1 to P 26 is PX 1 When the values of the vertical axis are represented by PY 1 to PY 26 and the ratio of the position of each point to W and H is represented by RX 1 to RX 26 and RY 1 to RY 26, respectively, Is determined as follows.

 , Horizontal axis

 W = (RX 26-RX 1)

 RX 1 = 0

 RX 2 = ((RX 2-RX 1) ÷ W) X 1 00

 RX 3 = ((RX 3-RX 2) ÷ W) X 1 00

RX 26 = 1 00

, Vertical axis H = (RX 22-RX 1)

 RY 1 = 0

 RX 2 = ((R Y 2 -R Y 1) ÷ H) X 1 00

 RX 3 = ((R Y 3 -R Y 1) ÷ H) X 1 00

R Y 22 = 1 00

 RX 23 = ((R Y 23 -R Y 1) ÷ H) X 1 00

RX 26 = ((R Y 26 -R Y 1) ÷ H) X 1 00

[0055] In this case, the whole is expressed as 100 and expressed as a percentage, but the unit of the ratio is not limited to this.

 Similarly, values such as length, inclination and vectors between points can be obtained. Furthermore, for example, for all points, P 3, P 13, P 22 and P 1, P 7, P 17 and P 26 respectively are compared with the previous and subsequent values, respectively. It can be extracted as a candidate or low price candidate as a point that represents the feature of the waveform.

The waveform connecting points representing the features of the waveform is as shown in Fig. 3 (b). At this time, for example, each of the line segments connecting the points can be represented as L 1, L 2, L 3, L 4, L 5, L 6. We can look at the features in detail for the line segments L1, L2, L3, L4, L5 and L6. That is, unlike the comparison of the prior art with the value at a specific point in time (for example, the present value, moving average value, change rate, deviation from moving average, etc.), a predetermined number of predetermined values of waveform data Predetermined relationships can be flexibly compared by abstract space (common measure). In particular, it relates to a predetermined point relationship corresponding to a predetermined value of waveform data, for example, a predetermined line obtained by connecting the predetermined points, and a predetermined shape such as a line and a predetermined point. It can be compared while holding the information. The predetermined point corresponding to the predetermined value of the waveform data may include a value obtained by processing the predetermined value such as a vector, and the predetermined shape may be a line, a line segment, a polygon, etc., in particular It doesn't matter. Also, the scope of the relationship is not particularly limited. For example, the predetermined shape may be extended beyond the range of the period of waveform data to compare the relationship of values and the relationship between the shapes.

 [0058] Then, a predetermined relationship of predetermined values, a predetermined shape, and their relationship, for example, L

 Each line segment of 1 to 6 can be replaced with a predetermined character string based on its own definition. For example, if the line segment is upward, it can be replaced by ten, and if it is downward, it can be replaced by one. In this case, it can be replaced with + _ + _ +-.

 [0059] Furthermore, the length of the line can be added. For example, if the ratio of the length of each line segment to the length of the shortest line segment L 1 is determined and they are regarded as an integral multiple of the approximate value, the waveform is as follows: +--+ + +--+ + + + Can be replaced by

 [0060] The character string to be replaced is not limited to + _, and may be replaced by an alphabet or another character, or may be replaced by a predetermined symbol or numerical value according to a unique definition. In this example, although the orientation was created based on the upper and lower sides and the length, the feature of the line segment may be defined in detail, such as angle or ratio, and replaced with a string defined to correspond to them.

Similarly, P 3, P 1 3, P 2 2, P 1, P 7, P 1 7, P 2 6, as shown in FIG. 3 (c), FIG. 3 (d), Each line segment can be replaced with a character string, for example, a line segment connecting each point.

 Also, the predetermined value, the relationship of the predetermined value, and the predetermined shape may be replaced with a predetermined character string.

 [0063] ♦ Overlaying ♦

 In addition, attributes used for definition may be used in combination other than those based on values representing the size of the waveform.

 For example, time series data of volume and trading value at the time of price fluctuation are similarly analyzed, and the minimum value of the size of trading volume and trading value is set to 1, and the ratio of the size to the minimum value is calculated. If you regard as an integer multiple of the approximate value, you can replace it with a string as well.

[0065] Furthermore, superimposing and considering those character strings, for example, A large stock price increase of gold increases the number of dozens, and a drop of large stock price of trading volume or trading value increases the number of ones, and conversion to a string having a new definition is also possible.

 [0066] Similarly, it may be converted into a character string in consideration of superposition of time series data such as market average value, stock index, industry average, credit transaction ratio, period of new moon and full moon, etc. . In addition, statistics on fluctuation patterns of another predetermined period (for example, whether the stock price rose, fell, or remained after a predetermined time series pattern) for time series data of a predetermined period If the probability of rise is high, the number may be increased, and if the probability is low, the number may be increased, such as increasing the number of ones.

 [0067] For superposition, conditions may be configured using Boolean OR (OR), AND (logical AND), NOT (NOT), exclusive OR (XOR), etc. It may be configured freely by adding a standard.

 For example, the waveform of the price is superimposed on the waveform of the trading value or the waveform of the trading volume, and the correlation of the past fluctuation with the Nikkei Stock Average (when the Nikkei Stock Average is rising at the same time) Often, or the other way around, etc.) is superimposed on the waveform of the statistical value, and there is little correlation with the fluctuation of the yen / dollar rate (eg, the influence of the weak yen or yen is small) For example, multiple abstract spaces and strings may be superimposed and configured freely.

 [0069] ♦ Statistics and simulation ♦

In addition, the computer terminal, as a statistical storage means, analyzes the time series data of a predetermined period as the statistical storage means, and detailed statistics of fluctuation patterns of another predetermined period, or buys and sells when the time series data appears. You may calculate detailed statistics if it was done and save it in a storage area. For example, the maximum rise width, the maximum fall width, the number of rise and fall and leveling and the ratio, the profit and loss ratio at the time of hypothetical trading, the maximum loss, the maximum profit etc. When storing time-series data of a predetermined period from the computer storage area, their statistical values may also be extracted at the same time. Note that data association There is no limitation on the method of For example, data representing the association may be stored together with the associated data, or the association may be performed by a predetermined method when retrieving the data. Also, the data storage location may be one or more than one.

 [0070] A simulation apparatus of time-series economic data may be created by the above-described method of storing and retrieving detailed statistical values of variation patterns of another predetermined period with respect to time-series data of a predetermined period. Good. This simulation device has an effect different from that of the prior art, that simulation results can be obtained in a short time.

 That is, the simulation apparatus for time-series economic data of the prior art starts calculation for simulation after entering the conditions, and it takes a relatively long time to increase the amount of data. The simulation device of the time-series economic data according to the present invention only needs to retrieve the statistics of time-series data of another predetermined period stored in association with the time-series data of a predetermined period from the computer storage area. . The greater the amount of data, the greater the difference between this technology and the existing technology.

 [0072] ♦ equivalent condition ♦

 Next, a method of comparing economic time series waveform data replaced with a predetermined character string and an equivalent condition will be described.

 [0073] A predetermined character string generated from economic time series waveform data can have its own equivalent condition in the abstract space. For example, the equivalent condition can be considered as multiple conditions as follows.

 Condition 1 ■ ■ ■ If the character strings of the waveform W 1 and the waveform W 2 are the same, the waveform W 1 and the waveform W 2 can be regarded as equal. For example, if the waveforms W 1 and W 2 have the following relationship, they are considered equivalent.

 W 1: + _ + _ + _

 W 2: + _ + _ + _

[0075] Condition 2 ■ ■ 'It is judged that the context of the character string of waveform W 1 and waveform W 2 is similar If possible, the waveforms W1 and W2 can be regarded as equivalent. For example, if the waveform W1 and the waveform W2 have the following relationship, they are regarded as equivalent.

 W1: + _ + _ + _

 W2: + + __ + + + _ + +

 Condition 3 ■ ■ 'If the ratio of the different portions of the character strings of the waveform W1 and the waveform W2 is within a certain value, the waveform W1 and the waveform W2 can be regarded as equal. For example, if the waveforms W1 and W2 have the following relationship, they are regarded as equivalent.

 W1: + _ + _ + _

 W2: + _ + _ +

 (There is only one difference in W2 compared to W1.)

Condition 4 ■ ■ ■ If it can be recognized that there is a common rule in the number of character strings of the waveform W1 and the waveform W2, the waveform W1 and the waveform W2 can be regarded as equivalent. For example

If the waveforms W1 and W2 have the following relationship, they are considered equivalent.

 W1: + _ + _ + _

 W2: __ + + + + + __ + + + +

 (W1 is 10 for three and-is for three. W2 is ten for eight and-is for eight. The commonality is that the numbers of W1 and W2 are equal. is there. )

Condition 5 ■ ■ ■ If it can be recognized that there is a common rule in the symmetry of the character strings of the waveform W1 and the waveform W2, the waveform W1 and the waveform W2 can be regarded as equivalent. For example, if the waveforms W1 and W2 have the following relationship, they are considered equivalent.

 W1: + _ + _ + _

 W2: _ + _ + _ +

 (W2 is the same as W1 when replacing the positions of ten and one.)

As described above, it is possible to uniquely define the criteria by which the waveforms are judged to be equivalent or not equal in human judgment, and computer instructions corresponding thereto can be prepared.

[0080] ♦ Search ♦

For string crawling, see B inary T ree (binary tree) and B_T r Documents are indexed by an algorithm such as ee (balance tree), and a specific character string is searched out from many documents and databases, a document containing a specific character string, or data associated with a specific character string A character string search technology is known that searches for characters quickly.

 As described above, the present system may have a mechanism for arranging a set of time-series values in an abstract space, converting it into a character string, and storing it in a computer storage area. Furthermore, as with string search technology, it may have a mechanism for fast retrieval from computer storage. There are no particular problems with the algorithm or mechanism for taking out.

 Similarly, in the present invention, a string search technique is applied, and a set of time series values is used as a search query to search for equivalent economic time series waveforms. You can search for any time-series economic data associated with the string by searching for.

 Furthermore, the present system may search for arbitrary time-series economic data by comparing numerical values constituting an abstract space without substitution by strings.

Further, the present system may create an equivalent condition by comparing numerical values constituting an abstract space with reference to the generated character string.

[0085] ♦ Condition level of error range ♦

 First, it has been described that it is possible to uniquely define a plurality of criteria in which the waveforms are judged to be equal or not equal. Next, a technique for covering the plurality of equal conditions will be described.

For example, when W 1 is a waveform input by designating a range from a chart, and W 2 is a waveform of actual stock price fluctuation data, condition 1 to condition

As shown in 5, it is possible to determine whether a predetermined equivalent condition is met or to search for a waveform that matches.

Also, conditions can be newly created by combining conditions.

For example, conditions can be newly classified as follows according to the combination of the conditions of Condition 1, Condition 2, and Condition 3. • Condition A ■-■ When only condition 1 is satisfied

 • Condition B ■-■ When only condition 2 is satisfied

 • Condition C ■-■ When only condition 3 is satisfied

 • Condition D ■ • When Condition 1 and Condition 2 are satisfied

 • Condition E ■ • When Condition 1 and Condition 3 are satisfied

 • Condition F ■ • ■ When condition 2 and condition 3 are satisfied

 • Condition G ■-■ When condition 1 and condition 2 and condition 3 are satisfied

 [0088] How to decide the combination condition is that even if the condition is configured using Boolean OR (OR), AND (AND), NOT (not), exclusive OR (XOR), etc. It may be configured freely by adding predetermined criteria. For example, conditions such as “when condition 1 or condition 2 are satisfied” may be created.

 Furthermore, when expressing the level of tolerance as a variable LEVEL, condition A to condition G can be made to correspond to any level of tolerance as follows.

 ■ Condition A ■ ■ ■ Level of tolerance 0% to 80% (80> = LEVEL> 7 0)

 ■ Conditions Β · ■ ■ Tolerance level 60% to 70% (70> = LEVEL> 6 0)

 ■ Condition ■ ■ ■ ■ Tolerance level 50% to 60% (60> = LEVEL> 50)

 ■ Condition D '■ ■ Tolerance level 40% to 50% (50> = LEVEL> 4 0)

 ■ Condition E ■ ■ ■ Tolerance level 30% to 40% (40> = LEVEL> 3 0)

 ■ Condition F ■ ■ ■ Tolerance level 20% to 30% (30> = LEVEL> 2 0)

■ Condition G ■ ■ ■ Tolerance level 1 0% to 20% (20> = LEVEL> 1 0) [0090] Correspondence between the condition and the level of tolerance may be configured freely by setting predetermined criteria for each system.

 [0091] In this example, seven conditions are listed, but finer features may be added to increase the combination of conditions and provide many stages. For example, different conditions may be defined each time the level of tolerance changes by 1%, or different conditions may be defined every 0.010 1%.

 Further, even if statistics of predetermined values and time series of values are taken at a predetermined time, the statistics are stored in a computer storage area, and conditions are dynamically configured using those statistics. Good. For example, when time-series economic data is newly input to the system, such as the latest price information, the number of waveforms that apply to each condition is automatically analyzed using a frequency distribution, and the tolerance error at that time is analyzed. Conditions may be defined so that the distribution of each level is approximately equal, or a level of tolerance is created based on periodically collected statistics, and the level of tolerance is dynamically configured. May be With the above-mentioned configuration, it is possible to obtain the effect of performing flexible analysis corresponding to the latest economic time series data while preventing deviation of the tolerance level. In addition, as a statistical means for obtaining statistics, a predetermined component for obtaining statistics may be newly provided, or the abstract space arrangement component 12 may be used. Also, the system and method for taking statistics and creating conditions may include human work, and it does not matter in particular.

 [0093] ♦ Upper and lower limits of the condition level of the error range ♦

 In addition, the correspondence between the tolerance value and the equivalent condition indicates that the lower limit of 0% does not match any waveform when the range of the tolerance value is 0% to 100%. The upper limit to the lower limit of all equivalent conditions can be expressed by making the upper limit of 100% correspond to all waveforms, corresponding to the equivalent conditions.

[0094] Furthermore, while the magnitude of the range of equivalent conditions is changed stepwise between the upper limit and the lower limit, by configuring the equivalent conditions corresponding to the value of each tolerance, the condition with less leakage can be obtained. You can create a specified method. Low leakage condition The specified precision depends on the graded precision of the equivalent condition between the upper and lower limits.

 As described above, for example, it becomes possible to perform waveform matching processing with a specified range of error and flexibility without losing the waveform characteristics as shown in FIG. Figure 4 (B) is the equivalent condition for the arbitrary waveform Win shown in Figure 4 (A). For example, if the user arbitrarily inputs from an error range input component 1 2 3 as an error range input unit, such as an allowable error level 1 0 0 for an arbitrary waveform W in, an equivalent condition component 1 as an equivalent condition storage unit 1 The predetermined equivalent condition corresponding to the tolerance level of 10% is selected by 24 and the limit of the other range of the waveform W up representing the range of the predetermined equivalent condition and the other range of the predetermined equivalent condition is selected. If the waveform is determined by the waveform W down, it can be determined that the waveform is the same waveform, and the waveform can be flexibly scanned by changing the value of the tolerance level between the lower limit and the upper limit. Can. As already described, the present technology allows the equivalent conditions to be freely configured by definition, and FIG. 4 is an abstract arbitrary waveform diagram for explanation. However, it is not always possible to recognize equal waveforms by being between two waveforms or by the distance between the waveforms. For example, as described above, there may be a combination of free definitions and free definitions such as the above conditions F and G.

 [0096] ♦ Time-series economic data and simulations sought by investors ♦

 Also, in general, waveform patterns of time-series economic data required by users such as investors and trading conditions are not always clearly recognized in advance by the users. Information required by users such as investors mainly comes from buying and selling timings and stocks that are likely to be profitable. These were historical statistics and were confirmed after the fact, and it is not always known that a profitable trading method exists.

 Therefore, a user such as an investor may, for example,

It is possible to input vaguely an image of a waveform that can specify a predetermined range in a bag or make profitable trading. [0098] Rather than returning vague output for this vague input, the present invention finally aims for the user while approximating the correct output for vague input. The output can be clarified and returned.

 [0099] This is, for example, the effect brought about by the search technique described above, the tolerance level setting technique, and the precalculation (statistical value) of the simulation result.

 That is, by stepwise changing the condition of the tolerance of the waveform without leakage, the user scanned all the waveforms in the computer memory in a short time, and attached the information of the waveforms. Optimal input values can be adjusted based on the output of trading simulation information.

 That is, by taking past and present time series economic data as input waveforms, inputting each value as a time series set, expressing the relationship between each point as a ratio, and converting it into a character string or the like. At the same time, when placing in an abstract space, determine the ratio of waveform variation in another predetermined range, take statistics, associate the statistics with the original predetermined waveform, and save in the computer storage area. The statistics associated with the search results waveform for the input waveform can be used immediately.

 [0102] Therefore, the user can immediately obtain the output for the input, and by repeating the adjustment of the input, it is possible to create a desired trading rule in a short time and use the statistics immediately. Become.

The statistical value may be displayed to the user through a web browser or the like, or may be used as a determination condition when issuing a computer instruction of a trade order.

In addition, at the time of the search, the search may be performed within a predetermined range of the computer storage device, such as the limitation of the market or the limitation by the attribute of the brand.

[0105] As a method of simulation, in contrast to the conventional method performing calculation after specifying a condition, the present invention relates to a statistical value from a computer storage area in which a statistical value was stored at the time of analysis of a waveform. Since it is possible to take out the results of the simulation in a very short time.

Also, in the case of the conventional method, the simulation is performed by inputting values or calculating While specialized knowledge about statistics and mathematics is required for specification, analysis of output results, etc., the present invention allows mice, cursors, etc. to be used even if they have no specialized knowledge at all. The slight manipulation of the computer input device can easily output the simulation results.

 [0107] ♦ Summary of core part explanation ♦

 As described above, the present system is flexible in pattern matching, search processing, and simulation while maintaining the waveform characteristics of the various time-series economic data with the shape of the waveform being significantly different from the prior art. Can be done.

[0108] ♦ Description of server and client ♦

 FIG. 5 is a schematic diagram of a network in which systems and methods may be implemented in accordance with the principles of the present invention. A network 10 is an environment in which data communication is performed, and a plurality of clients and a plurality of servers may transmit and receive data. This network may include a combination of Local Area Network (L A N), Wide Area Network (W A N), Telephone Network, Intranet, Internet, Storage, Network, etc.

20 clients are terminals for data communication, and devices such as personal computers, PDAs, laptop computers, mobile phones, other computers and communication devices, threads installed in these devices, and so on. It may be defined as a process or an executable object within these devices. Whether wired, wireless, optical, or connected, data may be transmitted and received to one or more servers, constantly or temporarily, via a network.

A server 30 is a terminal that performs data communication in response to a request from a client, and is a device such as a personal computer, a PDA, a notebook computer, a mobile phone, other communication devices, and communication devices. It may be defined as an internally implemented thread, an application executable in these devices, or the like. Whether wired, wireless, optical, or other connection method, you can connect to one or more clients, always or temporarily, through the Internet Data may be transmitted and received.

In the above-described server'client configuration, efficient data communication may be performed. For example, when there are many situations where each terminal refers to the same information resource, storing each terminal will result in a great deal of waste in terms of storage area and maintenance. The server is the means to solve this, and a specific terminal manages the information and its processing intensively to minimize the storage area of the whole network and to share the information. It saves time and effort such as synchronization and improves the efficiency of information transmission and maintenance. In addition, each terminal may concurrently use a server simultaneously with a client, or a plurality of terminals may constitute one client or server.

[0112] ♦ Computer Description ♦

 FIG. 6 is a schematic diagram of a computer terminal 40 on which systems and methods may be implemented in accordance with the principles of the present invention.

 Each computer terminal 40 may perform data communication as an element of the above-described server / client configuration. Each computer terminal 40 is a processor 4 1, a storage device 4 2, a main memory 4 3, a read only memory (ROM) 4 4, one or more input devices 4 5, one or more outputs Device 46, communication interface 47, and bus 48 may be provided.

 The processor 41 is a device that performs arithmetic processing, and may have one or more normal processors or microprocessors that analyze and execute instructions called machine language.

[0115] Storage device 42 is a series of addressed storage areas, each storage area storing a small amount of information, which in some cases tells the computer what to do The instruction may be data that the computer is to execute the instruction. The storage device 42 may be a magnetic or optical disk or a tape, or may be a non-volatile flash memory in which data is not erased even when the power is turned off. The storage device 42 may also be equipped with a device for reading and writing data. [0116] The main memory 43 is a storage device to which the processor 41 can directly access, and is a row of addressed storage areas, and each storage area stores a small amount of information. In some cases, this information may be an instruction that tells the computer what to do, or it may be data on which the computer executes the instruction.

 [0117] Read Only 'Memory 4 4 is a read only storage device that may store static information or static data or instructions used by processor 4 1

The input device 45 is a device by which the user of the computer terminal 40 transmits information to the computer terminal 40, and the computer terminal 40 includes one or more input devices 45. It is also good. For example, the input device 45 includes a keyboard, a mouse, a pen tablet, a microphone, a touch panel, and a track pole.

 The output device 46 is a device for transmitting information from the computer terminal 40 to the user of the computer terminal 40, and the computer terminal 40 is provided with one or more output devices 46. May be For example, the output device 46 includes a display, a printer, and a speaker.

 The communication interface 47 is a device that enables the computer terminal 40 to communicate with other terminals and systems. For example, the communication interface 47 includes Ethernet (registered trademark) and wireless devices. There are no particular limitations on the method, such as using electricity, light, infrared light, or magnetism.

 [0121] A bus 48 is a bundle of wires connecting the respective devices of the computer terminal 47 to each other to transmit data.

In the configuration as described above, the computer terminal 40 in accordance with the principle of the present invention performs a specific operation as shown in FIG. The computer terminal 40 may perform these operations in response to the processor 41 executing software instructions contained in a readable medium such as the main memory 43. The software instruction may be read into the main memory 43 from another readable medium such as the storage device 42 or from a predetermined device via the communication interface 47. The processor 41 may cause a predetermined process in accordance with the principles of the present invention by means of software instructions in the main memory 43.

 Alternatively, hard-wired electrical circuits may be used in place of or in combination with software instructions to implement processes consistent with the principles of the invention. Thus, implementations consistent with the principles of the invention are not limited to any specific combination of hardware circuitry and software.

 As described above, a predetermined process in accordance with the principle of the present invention can be implemented, for example, in a computer terminal 40 of a predetermined server 'client configuration.

For example, as shown in FIG. 7, a waveform input component 12 1 and an error range input component 1 2 3 are configured on the computer terminal 40 of the client 20, and an abstract space arrangement component 1 2 2, Comparable condition component 1 2 4, comparison matching processing component 1 2 5, action trigger component 1 2 6 are configured on computer terminal 40 of server 30, and communication terminal 4 through computer interface of client 20. 4 0 to server 3 0 computer terminal 4 0 transmits the set of time series values constituting the input waveform and the value of the error range as a search query, and the server 3 0 computer terminal 4 searches them Search economic waveform data and statistical data stored in the storage device corresponding to the query, and use the action trigger component 1 2 6 Through communication interface 4 7, time-series economic data and statistical data of search results may be returned. The communication protocol may be HTTP (Hypertext 卜 Lancer 'Protocol), or encrypted communication may be performed using SSL (Secure Socket Layer 1). A proprietary communication protocol may be used, or the communication interface 47 may be configured freely without using it. The computer terminal 40 is a personal computer, a workstation, a server In addition to a dedicated machine, a mobile phone with an internet connection function may be used, and the computer terminal 40 can be configured freely.

Further, for example, as shown in FIG. 8, the waveform input component 1 21 may also be configured on the computer terminal 40 of the server 30, and data of the economic data distribution service may be input. The data may be input from a component that acquires data, or may be input from the storage device 42 of the computer terminal 40 such as the main memory 4 3, the ROM 4 4, the hard disk, and the magneto-optical disk device.

 Next, three specific configuration examples of the system used in the present technology and their respective effects will be described.

[0129] ♦ Example 1 Search system ♦

 The first configuration example is a search system for time series economic data as shown in Figure 9.

[0130] For example, database 50 in FIG. 9 is a database for storing economic time series information, and stores information on prices and volumes of all listed stocks in Japan and the United States of a predetermined period. There is. Furthermore, the time-series data of all brands stored in database 50 are input to waveform input component 1 21 and, using the techniques described above, abstract space arrangement components 1 2 2 There may be one or more indexer components 51 to index through.

Indexing may be performed based on a character string generated from a waveform, or may be performed based on an arbitrary value as described above. The abstract space arrangement component 1 2 2 may calculate and arrange the dollar in the yen conversion to compare waveforms of economic data based on different currencies as well as coordinate system conversion, or It may be calculated and arranged by conversion, or an abstract unit which can represent all currency units may be defined, and all currencies may be converted and arranged into the predetermined unit. Furthermore, based on this abstract unit, in consideration of superposition due to fluctuations in exchange rates, placement in an abstract space according to fluctuations in exchange rates may be performed to generate a corresponding character string. . Further, the indexer component 51 may construct an abstract space in the database 50 or may newly create the database 52. The databases 51 and 52 may be created in the storage unit 42 of the computer terminal 40 such as the main memory 43, the ROM 44, the hard disk, and the magneto-optical disk unit, or on a plurality of computer systems. It may be created separately. The economic time series information stored in the database 50 may be not only past data but also real time data, or may be directly input to the waveform input component 1 2 without being stored in the database 50. Placement in an abstract space may be performed through 1. In addition, the database 50 may automatically call the indexer component 51 to perform indexing automatically when storing economic time series information. The database 50 may store time series information of stock markets of all countries, not limited to Japan and the United States, and may be economic time series of all investment targets such as exchange, futures market, etc., not limited to stock markets. Information may be stored. In addition, not only price information, but also time series data of corporate financial statements, time series data of statistical data such as economic indicators, and time series data of natural phenomena that may be related to supply and demand of the commodity futures market. It may be included. As described above, this system can handle all of the time series economic data, which may be huge, with the simple mechanism of the waveform input component 12 1 and the error range input component 1 2 3 it can. The waveform input component 1 2 1 is a device for inputting a set of time-series values, and may be in a form that can input an arbitrary waveform as shown in FIG. 2 (b) with a mouse, for example. 2 (c) may be specified by specifying the range of the chart with a cursor or a mouse, or a representative waveform may be registered in advance, and it may be performed by selecting them. The waveform input component 1 2 1 may be used with the error range input component 1 2 3 or may be used alone. The error range input component 1 2 3 may correspond to the equivalent condition indicating that the lower limit does not match any waveform, and may correspond to the equivalent condition indicating that the upper limit matches all waveforms.

Note that the present system is based on the Nikkei average stock adopted by the TSE of the Japanese stock market. Or, it may be used with a limited scope, such as corn in the Chicago Commodity Futures Market.

 By the above configuration, the present system exhibits the following effects.

 First, with a set of time-series values as a search query, it is possible to select waveform data meeting the equal conditions from time-series economic data that may be huge. Furthermore, it is possible to scan all time-series economic data, which may be huge, by adjusting between the lower limit and the upper limit of the error range for a search query of a set of values of any one time-series. it can. In comparison with the conventional technology, this technology can be said to be extremely simple in structure compared to the amount of information that can be processed. In addition, because it is simple, it can be said that it is a mechanism that can be used by a wide range of users with low hurdles involved in using the system. Also, in the case of the prior art, it is necessary to visually check the chart after sorting by moving average value, technical index value, profit increase rate, etc. In order to see the need for power, the Japanese stock market and the US stock market, stocks and bonds, foreign exchange, futures, multiple correlations, and even greater effort and time. It may be necessary to use judgment power, but in this system, it is possible to handle time-series economic data, which may be huge, beyond the differences between countries and markets, investment targets, etc. It can be said that it has a great effect.

 Example 2 Simulated Trading, Automatic Trading System ♦

 The second configuration example is a mock trading system and an automatic trading system.

 [0137] In the case of automatic trading according to the prior art, there has been a method of processing an order having a condition based on a value, such as when the price or time has reached a predetermined value. Although it reduced, it did not reduce the effort of investment judgment and investment analysis itself. In addition, there was a method of trading automatically by specifying the condition, but the condition was complicated, the condition was fixed, the investor was not necessarily satisfied, and the chart It was common to make buying and selling decisions by looking at it.

Also, in the apparatus for analyzing economic data, attributes such as brand name and market, etc. Such as moving average value, technical index value, fundamental information value such as financial statement value, value change rate value, value divergence rate value etc. Although they have certain effect when selecting investment object by value, it is same Even if the value of the target is selected, a number of different targets are selected, so by looking at many charts in the end, it is necessary to analyze the details, and although the amount of the selected is reduced, the visual confirmation Time and labor to make the

 In addition, in devices that display economic data, candlesticks and marks are added.

There is a configuration method that provides an easy-to-see display by classification by values such as color coding, moving average values, technical index values, statistics, etc. However, although certain effects can be obtained, classification method, display method, size of display area It is necessary to analyze the details if the amount of information is limited or if you look at many charts in the end, etc. Although the amount of information displayed is reduced, visual observation It took time and effort to confirm and make decisions.

 In addition, in equipment that carries out trade simulation, in order to set conditions, it is necessary to understand the meaning of conditions, or knowledge about mathematics and statistics is required, and specialized knowledge The hurdle needed was high. In addition, it took a long time to calculate the simulation after setting the conditions, requiring a high-speed computing device. In addition, when fine-tuning the conditions, it took a long time for recalculation and a large amount of effort for analysis.

In this configuration example, first, a waveform representing the timing of buying from waveform input component 1 121, a waveform representing the timing of selling, and a waveform from error range input component 1 2 3 Create trading terms by entering the tolerance range of. The input waveform is arranged in the abstract space by the abstract space arrangement component 1 2 2, and is regarded as equivalent to the predetermined waveform by the equivalent condition component 1 2 4 and the comparison matching processing component 1 2 5 as the equivalence judgment means. It has already been described that it is possible to select out a predetermined waveform that can be made or to judge whether the predetermined waveform can be regarded as equal to the predetermined waveform. Then, through the compare and match processing component 125 The decision on trading conditions is made, and the action trigger component 1 2 6 executes a predetermined instruction based on the result of the decision. In this case, the results of simulated trading and simulation are sent back to the computer terminal 40 of the client 20, or actual trading orders are made.

 When simulated trading is performed, waveforms stored in the storage area of the computer terminal 40 such as the database 50 and database 52 shown in FIG. 9 or waveform input components 12 1 can be directly input from It performs comparison matching processing between the waveform of the latest actual price data and the waveform input by the user, and performs processing for extracting statistical values that may be stored in the storage area of the computer terminal 40. A vague trading condition is input so that the statistical value of the simulated trading result can be immediately taken out of the storage area of the computer terminal 40 for the trading condition input by the user without having to calculate it for a long time Even if it has been flexible, it has already been explained about the effect of being able to approach trading conditions desired by more specific users. Next, a more specific configuration will be described, and other effects of this configuration will also be described.

 First, the main processing system of the commodity trading system according to the present invention will be described.

 [0144] Buy products with fluctuating prices (specifically, stocks, bonds, mutual funds, foreign currency products, currency exchange, commodity futures, index futures, options, deliveries, precious metals, etc.) at the bottom price and sell at the highest price If you sell or borrow what you borrowed at the highest price and repurchase at the bottom price, you will experience the greatest interest. Although the day traders and investors are trading on a daily basis while analyzing complex and huge information for the purpose of this purpose, it is very difficult to determine the timing of trading, and it is difficult to find any fluctuation in price. It is.

In addition, the past price fluctuation data for each product brand may include information that clearly indicates the bottom price or the precursor of the highest price, and this apparatus is configured to be used for arbitrary purchase input by the user. The trading timing is determined based on the waveform data and sales waveform data, trading simulation is performed according to the timing, and simulated trading results are output. In addition, when a favorable result is obtained in the trading simulation, the present apparatus determines the input waveform data, and based on the trading timing determined from the real-time price fluctuation data, the apparatus actually carries out price fluctuation goods. Perform trading.

 Next, input of waveforms representing the timing of buying and selling will be described. For example, in general, daters and investors look at time-series charts, measure timing, and make investment decisions. As described above, the user can input a predetermined waveform by means of a predetermined input device 45. For example, by moving the mouse, the position information of the mouse can be used to input a waveform having the same shape as the waveform displayed on the chart. Also, the user can associate predetermined information with this waveform according to a predetermined computer command, and store the information in the storage device 42 of the computer terminal 40. For example, add information such as whether the given waveform is a buy waveform, a sell waveform, a price waveform, a volume waveform, or an operating profit margin waveform. It can be stored on computer storage. It has already been described that the present technology can flexibly perform pattern matching, search processing, and simulation while maintaining the characteristics of the waveform to such an extent that the shape of the waveform is significantly different from that of the prior art. Therefore, the user compares the waveform stored in the storage unit 42 of the computer terminal 40 with the waveform of the time-series data of actual price fluctuation, and configures the condition judgment by the comparison matching process described above. It is possible to use it as the timing of trading without visually judging the same waveform shape again. Also, as described above, it is possible to create trading conditions by superimposing waveforms of various conditions. Of course, conditions based on values such as market type, investment amount, operating profit margin, and technical indicators may be combined to create trading conditions.

 FIG. 10 illustrates six representative waveforms of the shape of the line that the user wants to find.

[0149] Figure 10 (A) shows that the middle is the lowest and the same low values exist before and after It is a waveform.

 [0150] Figure 10 (B) shows a waveform with warpage.

 [0151] FIG. 10 (C) is a waveform that jumps sharply.

 [0152] Figure 10 (D) is a waveform that rises sharply at a steep angle.

 [0153] Figure 10 (E) is a waveform with two as high values.

 [0154] Figure 10 (F) is a waveform with two as low values.

 [0155] Since the investor who confirmed the shape of Fig. 10 (A) has confirmed the low price range three times, the investor who has confirmed that it is difficult for them to fall further and forbids to invest It is possible to make a judgment that there may be a possibility.

 [0156] An investor who has confirmed the shape of Fig. 10 (B) has determined that there is a possibility that he may invest as he thinks that the price may rise because the price is gradually rising. There is a possibility.

[0157] An investor who has confirmed the shape of FIG. 10 (C) may think that it is desirable to sell it before the price falls, because the price has dropped sharply. It can be determined that there is no.

[0158] An investor who has confirmed the shape of Fig. 10 (D) judges that there is a possibility that they may invest, thinking that there is a reason for the price to rise because the price has risen sharply. There is a possibility.

[0159] Since the investor who confirmed the shape of Fig. 10 (E) has confirmed the low price range twice, the investor who has confirmed that it is difficult for them to fall further and forbids to invest It is possible to make a judgment that there may be a possibility.

[0160] Since the investor who confirmed the shape of Fig. 10 (F) confirms the high price range twice, the investor who confirms that it is difficult for the customer to go up more and does not go up sells for sale There may be a judgment that it might be considered desirable.

[0161] When processing the waveform as described above according to the prior art, as described above, it is difficult to sufficiently recognize the characteristics of the waveform, and the timing is measured while looking at the time-series chart. It is common to make investment decisions, and users It can be said that investment was forced to be made at the discretion of experience and sense. Fluctuations in prices can sometimes give users profits and losses and diminish their cool investment decisions. If this technology is used, it has the effect of being free from such a moment, labor, time to look at the chart. In addition, prices may depend on demand and supply, so prices may rise if there are many people who want to buy. Therefore, if there are more and more people who want to buy, if you buy quickly, you will get profit after purchasing. Since this technology is generally determined by visual inspection of the chart as described above, many time-series waveforms, such as the entire stock market, are determined rather than the timing determined by visual inspection of the chart. Can be monitored. Therefore, this technology enables users to find relatively many investment targets and investment opportunities in a relatively short time. In addition, this technology can be used similarly for investment targets in different markets and different currency units, as described above. Therefore, this technology may be used for transactions called profiting, which combine profit and loss to determine profits or to use price differences as investment criteria. Also, as described above, unlike the prior art, this technology reduces the labor of investment judgment and investment analysis itself and enables ordering of trading orders without visual inspection of the chart. Therefore, the user can continue the desired investment activity for the desired period with little effort. For example, automatic buying and selling may be performed until the user instructs to stop the automatic buying and selling, or when loss exceeds a certain level, the automatic buying and selling may be stopped and a loss may be notified. In this case, until the notification of loss is given, the user can significantly reduce investment time and effort, and the reduced time and effort can be used effectively for activities other than investment. If the investment result is not as desired, it may be possible to switch to the mock trading and use the statistics to create trading conditions again, making it an ideal system for investors.

As described above, according to the present technology, it is possible to configure a system with higher practicability than the prior art. Example 3 Display Unit ♦

 The third configuration example is the economic data display system as shown in Fig.11. As explained above, this technology enables a system that enables ideal investment activities without having to look at charts. However, it is also possible to construct a new display using the present technology. This economic data display system is characterized by expressing a large amount of information such as the entire stock market in a small display area 200, focusing on the fact that multiple equivalent waveforms are found at the same time. The equivalent waveform grouping component as equivalent waveform grouping means classified into the same group, the function as a display means for displaying economic data icons, and the classified waveform and the attribute of the information related to the waveform The predetermined position is determined according to a predetermined condition while storing the position of the icon displayed in the area and the function as an associating means associated with the appearance and display position such as size, shape and color, and the predetermined position. And a display area characterized by continuously changing. For example, move to a central position while maintaining a relative position other than the central position. Note that this display area has a function of displaying a predetermined icon at a predetermined position and changing the relative position continuously while maintaining the positional relationship before movement, with the icons displayed in the area. It may be a projection of a rotating sphere on a predetermined plane, or it may be a three-dimensional sphere itself, a plane, or any shape. Also, while moving, the appearance and relative position of the icon may be changed at the same time by changing the attribute.

As described above, it is possible to search a waveform that can be regarded as equivalent or to be regarded as equivalent while retaining the characteristics of the waveform shape, using a predetermined waveform as a search query. It is possible to make a decision. Also, as described above, we can process a large amount of information, such as the entire market or multiple markets or multiple time-series economic data, in a short time from the acquisition of time-series economic data. be able to. Therefore, the present technology is based on the equivalent waveform grouping component, for example, the equivalent waveform of the entire Japanese stock market. It enables feature analysis of time series economic data with short delay time.

 Also, as described above, according to the present technology, a predetermined waveform, for example, a brand whose trading value has rapidly increased, or a brand whose price is rising rapidly, has a certain waveform. You can search for waveforms that can be considered equivalent to the shape.

 This economic data display system displays a waveform indicating a predetermined timing and a brand indicating a waveform matching a predetermined shape at a predetermined position of the display area, for example, at the center, while continuously changing the display area. It has a function.

 That is, since the waveform indicating the predetermined timing and the waveform that conforms to the predetermined shape change the shape over time, the waveform indicating the predetermined timing and most conform to the predetermined shape The brands that are used can change from moment to moment. In this case, while constantly changing the display area and displaying the most matching brand in the center, the stocks other than the matching brand are displayed with the relative display position substantially unchanged based on the matching brand. Do. Just rotate the globe and bring any city to the front, and display so that the city that was in front is away from the front. However, the display position may not necessarily be the relative display position before the change, since the position may be changed depending on the predetermined condition while the predetermined brand is displayed at the predetermined position, and other brands may also change the position according to the predetermined condition. Does not change at all. Rather, it simultaneously displays the appearance and position changes of multiple icons, and displays a fluid display that responds to ever-changing fluid information. Just as the earth rotates, it displays each icon based on both the absolute position and the relative position, just as people and objects are moving according to another standard.

Further, this economic data display system is represented by an icon for each target of economic data, and the equivalent condition of predetermined economic data is represented by a predetermined color, shape, position and movement of the icon, and the condition has changed. In the case of changing the color, shape, position and movement of the icon, if the change is not abrupt, the color, shape, position and movement of the icon will not be abrupt, for example, intermediate color, intermediate shape or intermediate Change the movement gradually, always The predetermined equivalent condition is characterized by the predetermined color, shape, position and movement.

 For example, in addition to the waveform equivalent conditions, a predetermined color and shape may be determined for each type (attribute) to which a security belongs, such as a banking securities sector or an information technology related sector. If the price ranges (attributes) such as 10,000 yen to 200,000 yen, or 1000 yen to 2000 yen can be regarded as equivalent, predetermined colors, shapes, and movements may be determined.

 In this case, in the case where a given brand has a plurality of features, the form representing that given brand may simultaneously include the respective features. For example, the color of the rising brand is red, the color of the falling brand is blue, the flat brand is shown in the middle of red and blue, and the change to the sharp rise shows a slightly larger shape. The area may be surrounded by a line for each sector or price, or the display position may be changed when the price range changes. Economic data satisfying the predetermined equivalent condition The icons representing may be displayed so as to be gathered at relatively close positions.

 [0171] In addition, the equivalent condition for grouping, the condition to be displayed in the center, and the function to make the color, shape, and movement be as desired by the user may be provided. Also, due to the continuous change of the display area, the brand farthest from the condition displayed in the center may be hidden behind the movable display area or may be displayed in the farthest position without hiding. Good. In addition, icons that meet the conditions may be displayed so as to be at a predetermined position instead of the center. For example, as shown in FIG. 11 (a), a state in which a predetermined waveform brand A is displayed at the center of the display area 200 because it can be regarded as equivalent to a predetermined condition. Then, as shown in Fig. 1 1 (b), the brand B that can be considered equivalent to the predetermined condition is displayed in the center, and the brand A moves to the end of the display area 200. It looks like it has changed.

With the above configuration, the present system enables the user to instantly grasp the state of the market that approximates the actual movement of economic economic data. For example, while the price waveform has been relatively flat, desired economic data such as stocks whose trading value is rapidly rising are always displayed in the center, while prices are falling, trading is low, etc. Although not shown in the center, stocks that do not meet the conditions may not be displayed in the center, but may exist in the display area. When the handle changes to a desired condition, it changes to a predetermined easy-to-see position, making it possible to instantly grasp how all brands are changing in parallel. In addition, in order to continuously display new states while retaining the impression of the previous state, it has the effect of marking the user with a large amount of information, including not only the attributes but also the transition of changes. In addition, it is possible to recognize the timing of buying and selling predetermined stocks as well as the entire market condition only by looking around the predetermined position center, so that the operation and burden on the user's display device is small. Nevertheless, they can recognize large amounts of information and trade simultaneously. Note that this economic data display system may simultaneously analyze different types of investment targets such as stock markets in multiple countries, futures markets, and targets with time-series economic data, and different movable displays. It may be displayed in the area, or it may be displayed in a predetermined color, shape and movement for each sector or price range, and as classified by displaying icons, color, shape and movement for each market or different types. May be changed to display on one movable display area.

 As described above, according to the present technology, it is possible to configure a more flexible system than before.

Claims

The scope of the claims

 [1] waveform input means for inputting waveform data as a set of time series values, equivalent condition storage means for storing equivalent conditions for considering economic data arranged in time series as equivalent to the waveform data, and An equivalence judging means for judging whether economic data is regarded as equivalent to the waveform data;

 The equivalence determination means, when a relationship between any one or more values of the waveform data and any one or more values of the economic data satisfies the equivalence condition. An economic data processing system characterized by being equivalent to the waveform data.

 [2] An error range input unit for inputting an allowable error which is a level regarded as equivalent, the equivalent condition storage unit stores the equivalent conditions respectively associated with the plurality of tolerances,

 The economic data processing system according to claim 1, wherein the equivalence judgment means makes the judgment using the equivalence condition associated with the tolerance error inputted by the error range input means.

[3] The level of the tolerance may be a level that considers all the economic data equal to the waveform data, a level that does not consider all the economic data equal to the waveform data, and The economic data processing system according to claim 2, characterized in that there are levels provided in stages.

[4] The economic data processing system according to claim 2, wherein the equivalence judgment means makes the judgment again each time the tolerance error is changed by the error range input means.

 [5] The system further comprises statistical means for taking statistics of the number of the economic data considered equivalent to the waveform data by the equivalence determination means with respect to the equivalent condition,

The equivalent condition storage means is configured to associate the equivalent condition with the tolerance so that the distribution for each level of the number of the economic data that the equivalent determination means considers equivalent to the waveform data has a predetermined distribution. The economic data according to claim 2, characterized in that it is changed based on the statistical value taken by the statistical means. Processing system.

 [6] A data conversion means for adjusting the waveform data and the economic data to a common scale by converting at least one of the waveform data and the economic data, comprising:

 The economic data according to claim 1, characterized in that said equivalence judgment means performs said judgment using said waveform data and said economic data adjusted to said common scale by said data conversion means. Processing system.

[7] The data conversion means matches the waveform data and the economic data with character strings in accordance with a predetermined rule, respectively, to match the common measure. The equivalence determination means replaces the value of the waveform data. The economic data processing according to claim 6, wherein the determination as to whether or not a relation between the character string and the character string obtained by replacing the value of the economic data satisfies the equivalent condition is made by character search. system.

[8] The data conversion means converts the waveform data and the economic data by converting at least one of the waveform data and the economic data when the waveform data and the economic data are price data of different currency units. The economic data processing system according to claim 6, wherein the economic data is made into price data of a common unit.

 9. The economic data processing system according to claim 1, wherein said waveform input means inputs, as said waveform data, data corresponding to a waveform within a designated range of the waveforms displayed on the screen.

 [10] The economic data is price fluctuation data of commodity stocks whose transaction prices fluctuate,

The economic data processing system is a system for simulating the result of hypothetical trading of the commodity brand, and the trigger for the trading is that the equivalence judging means regarded the price fluctuation data as equivalent to the waveform data. The economic data processing system according to claim 1, characterized in that:

[11] The method further comprises statistical storage means for taking predetermined statistics from the economic data with respect to data of a predetermined period among the economic data and storing the statistical values in advance before the start of the simulation.

 The economic data processing system is characterized in that the statistical value stored by the statistical storage means is displayed for data of the predetermined period as a simulation result when data of the predetermined period is used as the waveform data. An economic data processing system according to claim 10.

[12] The economic data is price fluctuation data of commodity stocks whose transaction prices fluctuate,

 The economic data processing system is a system for performing automatic trading of the commodity brand, wherein the equivalence judging means regards the price fluctuation data as being equal to the waveform data as a trigger of the trading. The economic data processing system according to claim 1, characterized in that:

 [13] The economic data processing system is characterized in that, in the case of a system for simulating the result of virtual trading of the commodity brand, inheriting the waveform data used in the simulation to the automatic trading. 1 Economic data processing system described in 2.

 [14] The waveform input means inputs, as the waveform data, purchase waveform data for specifying the timing at which the commodity brand is bought and sale waveform data for specifying the timing at which the commodity brand is sold.

 The economic data processing system is triggered by the fact that the equivalence judging means regards the price fluctuation data as being equivalent to the buying waveform data as an opportunity to buy the commodity brand, and the equivalence judging means deals with the price fluctuation data as the sales waveform. The economic data processing system according to claim 10, characterized in that the sale of the commodity brand is regarded as being equivalent to data.

[15] Equivalent waveform grouping means for classifying the economic data considered to be equivalent to each other by the equivalent judgment means into the same group, display means for displaying the economic data in a display area by an icon, and the icon Appearance and table 2. The economic data processing system according to claim 1, further comprising: an associating unit that associates the display position with the group.

[16] The economic data processing system according to claim 15, wherein the associating means associates the appearance and display position of the icon with an attribute of the economic data other than the group.

[17] The economic data processing system according to Claim 15, wherein the association means determines the relative appearance and relative position of the icons according to a predetermined condition.

 [18] The economic data processing system according to claim 15, wherein the associating means determines the icon at an absolute position in the display area with a predetermined appearance according to a predetermined condition.

 [19] The economic data processing system according to claim 15, wherein the display means continuously updates the display.

 [20] A waveform input means for inputting waveform data as a set of time series values, an equivalent condition storage means for storing equivalent conditions for considering economic data arranged in time series as equivalent to the waveform data, and Have the computer function as an equivalence judgment means for judging whether economic data is regarded as equivalent to the waveform data,

 The equivalence determination means, when a relationship between any one or more values of the waveform data and any one or more values of the economic data satisfies the equivalence condition. An economic data processing program characterized by being equivalent to the waveform data.