JPH0744529A - Prediction and transaction aid device for time series data relating to market transaction - Google Patents

Abstract

PURPOSE:To provide a device to provide data by which a flow of a market cost is surely grasped and which is used for a guide for investment or the like in the case of transaction in a stock market or the like. CONSTITUTION:The device is made up of an input section 2 consisting of a data entry section 2a entering time series data for market transaction and a key board 2b, a center line arithmetic operation section 4 making a center of inputted time series data as a smooth continuous line by spline function calculation, an upper lower line arithmetic operation section 5 calculating a probability in fluctuation of the time series data with respect to the center line as a predetermined upper lower limit line, a chart setting section 6 setting data of the arithmetic operation sections 4, 5 to a chart, and a processing section 3 made of an index setting section 7 entering the probability of the fluctuation of the center line to a set chart as an index, and an output section 8 displaying them with a display section 8a and a printer section 8b.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION This invention inputs time series data for trading and option trading in various markets such as securities markets including stock markets, commodity markets, foreign exchange markets, financial markets and futures trading markets. The present invention relates to an apparatus for predicting time series data relating to market transactions and a transaction support apparatus for accurately grasping the flow of prices and using them as guidelines for investment strategies and tactics.

[0002]

2. Description of the Related Art In the stock market and the like, various means are used as an index for expressing transactions in a time series, in which data is analyzed by a computer and various fluctuation factors and fluctuations are analyzed. Attempts have been made to use predictive devices that take account of this.

[0003]

However, in many of these prediction devices, the user inputs by his / her own judgment, and a method for making this judgment accurate is not incorporated. In addition, since the given time series data is used as it is for analysis or analysis, there is a drawback that it is not possible to accurately grasp the influence of fluctuations and sufficiently satisfy the prediction accuracy and efficiency. . For example, even if the buy instruction is successful, the sell instruction for it is too early and the price becomes 1.5 to 2 times higher after the sell instruction is issued, or the sell instruction is not issued in many cases. , Again, after the purchase instruction is issued 1
Since there are cases where it drops by 0% to 50%, most of the decisions had to be made taking into account the opinions of investment experts.

In view of the above circumstances, it is an object of the present invention to provide a time-series data forecasting and transaction support device relating to market transactions, which can be forecasted with a high degree of accuracy and efficiency. is there.

[0005]

In order to achieve the above-mentioned object, the time series data prediction and transaction support apparatus relating to the market transaction of the present invention comprises an input means for inputting the time series data of the market transaction and an input. A centerline calculating means for obtaining the center of fluctuation of the time series data as a centerline of a continuous smooth curve by spline function calculation, and irregular fluctuation of the time series data with respect to the centerline calculated by the centerline calculating means. Upper and lower limit line calculating means for obtaining the probability as a predetermined upper limit line and lower limit line, chart setting means for setting each calculated value of the center line and upper and lower limit lines in the chart, and calculating a required turning point of the set chart. Outputting the turning point calculation input means, the chart set by the chart setting means, and the turning point input by the turning point calculation input means, together with the time series data. Is characterized in that it has configuration and output means that.

In the present invention, time-series data for predicting time-series data and inputting to a market support device for market transactions includes existing stock broadcasts such as stock prices, commodity prices, dollar quotes or futures indices and personal computer communications. Individual time-series data etc. picked up based on communication means or economic articles, etc. The data can be manually input as appropriate using a keyboard or the like.

The present invention in which the center of variation of the input time series data is obtained as the center line of a continuous smooth curve by the center line calculating means employs spline function calculation. Generally, in spline function calculation as a statistical method, odd-order calculations such as cubic spline function, quintic spline function and seventh-order spline function are known. This is not preferable because the vibration of the curve increases. In this spline function calculation, the required statistical weight G set by the weight calculation means is input and calculated.

In obtaining the probability of irregular fluctuation of time series data with respect to the center line obtained by the center line calculating means by the upper limit line and the lower limit line, the range of the upper limit line and the lower limit line is the time series with respect to the center line. The probability of irregular fluctuation of data can be set to a plurality of values such as 1% to 95%, but it is desirable to calculate as 5% among them.

The output means outputs the respective charts and the turning points together with a chart showing the rising and falling width of the center line, a chart showing the trading volume, and a chart showing the daily bar and the hourly bar in a predetermined period unit. It is desirable to be able to separately output one or more charts such as a chart showing details of time-series data. By referring to each of these charts, it is possible to more accurately grasp the flow of time-series data in a market transaction and make prediction and transaction support advantageous. The above output means
Although it is displayed on both the display and / or the printer, it is usually most preferable to use both the display and the printer.

When the time series data of the market transaction input to the transaction support apparatus of the present invention is provided as an analog amount, the time series data is input to the transaction support apparatus in advance or in the transaction support apparatus of the present invention. , And performs analog / digital conversion and inputs as a digital amount.

The respective calculation means such as the calculation of the weight G, the calculation of the upper and lower limit lines, and the calculation for setting the ascending index and the descending index as the turning points are based on the following specific methods.

1) Weight calculation means According to the investment policy of long-term, medium-term, and short-term, the time series data to be calculated is designated as either monthly, weekly, or daily, and the designated time series data is regularly paired. The value of the smoothed cubic spline function is calculated by converting the numerical value and inputting the initial value of the weight G. The first-order differential value, second-order differential value, and third-order differential value of this calculated value are calculated. Each derivative naturally forms a smooth curve with several waves varying from positive to negative. The weight G is changed and repeated calculation is performed until each differential value satisfies the set limit condition. Then, the value of the weight G when the limit condition is satisfied becomes the weight optimized according to the flow of the time-series data.

2) Means for calculating upper and lower limit lines In this case, the logarithmic value is also used for calculation in the same manner as described above, and the value is converted into a natural value and outputted. High and low prices of time series data and smoothed cubic spline function values (center line)
If you take the difference from and aggregate it, it will approximate a normal distribution curve, so
Calculate the standard deviation of this difference. In this calculation, the value 1.96 multiplied by the standard deviation at 50% on one side of the standard normal distribution table is 0.47500, that is, 47.5%. Therefore, the probability of taking a value of 1.96 or more multiplied by this standard deviation is 2.5%. Then, if 50% on one side of the standard normal distribution table is expanded to 100% and newly defined, the probability of taking a value of 1.96 or more of the value multiplied by the standard deviation is 5
%. Therefore, (center line + standard deviation) x 1.9
Line 6 has a 5% probability of being above this line. In this way, each% line between 1% and 95% can be calculated, which allows the upper and lower limits to be calculated.

3) Calculation means for index of increase When a common logarithmic value of time series data is calculated several times by the exponential smoothing method, a smooth curve is obtained. This curve is linked to the smoothed cubic spline function value, the natural time series data, and the natural trading volume, and only when the set conditions are satisfied,
Output the index of rise.

4) Calculating means for the index of decline The common logarithmic value of the time series data is exponentially smoothed. Only when the condition set by linking the exponential smoothed value and the smoothed cubic spline function value is satisfied, the index of the descent is output.

In this way, by linking the rising and falling indices with the smoothed cubic spline function value and outputting them under the set conditions, only the merit of each value is output, and the maximum effect is obtained. It is something to demonstrate. In the calculation using the common logarithm, the base of the logarithm is 10, and even if the base is a base e of natural logarithm or a value of 2 to 100, the calculation effect is almost the same, but the calculation using the common logarithm is performed. preferable.

[0017]

In the time-series data prediction and transaction support device relating to the market transaction of the present invention, the time-series data for the market transaction is input by the input means, and the center of fluctuation of the input time-series data is calculated by the center line. Means for calculating a smoothed center line by means of spline function calculation, particularly cubic spline function calculation, and the upper and lower limit line calculation means for determining the probability of irregular fluctuation of the time series data with respect to the center line. Calculate the upper and lower limits of the range,
The center setting, the upper limit line and the lower limit line are calculated by the chart setting means so that the calculated values can be represented as a chart, and the required turning points of the set chart are calculated by the turning point operation input means. The chart set value and the turning point thus input can be output together with the time-series data by display means and / or printed out. Therefore, based on these output data, it is possible to accurately predict the flow of market transactions and accurately determine the timing of actions such as buying, selling, and waiting. At that time, together with the output of the chart and the turning point, the chart showing the footstep of the time series data in a predetermined period unit on a daily basis, an hourly basis, a chart showing the trading volume and a chart showing the range of rise and fall of the center line. Output one or more of them separately,
By referring to these, prediction of time series data and transaction support can be further enhanced.

[0018]

[Embodiment] Hereinafter, as an embodiment of a time series data prediction and transaction support device relating to a market transaction of the present invention, a time series data prediction and transaction support device relating to a stock market transaction will be cited with reference to the accompanying drawings. It will be specifically described. Figure 1
The time-series data prediction and transaction support device 1 (hereinafter, simply referred to as the support device 1 in this embodiment) related to market transactions shown in the block diagram of FIG. And a processing unit 3 for performing arithmetic processing on the input time-series data and setting it as predetermined data, and an output unit 8 for outputting the arithmetically processed data.

The input unit 2 receives the time-series data by character broadcasting, personal computer communication, or the like, or the time-series data for manual input as information, and inputs it as a data acquisition unit 2a.
And a keyboard 2b for operating the setting and instruction of the capture condition when inputting to the capturing unit 2a, the setting and instruction of the processing condition in the processing unit 3 and the output instruction of the display and the printer, and the time series data. When manually inputting, data may be input by operating the keyboard 2b.

The processing unit 3 includes a center line computing unit 4 for setting a center line of the irregular fluctuation of stock prices as a center line smoothed by spline function calculation based on the time series data input to the input unit 2. An upper / lower limit line calculation unit 5 for calculating and setting an upper limit line and a lower limit line with respect to the center line obtained by the center line calculation unit 4, and a chart setting unit for setting the center line and the upper / lower limit line as a band chart. 6 and an index setting unit 7 for calculating and setting a change prediction index at the set change point of the chart. Basically, each processing in the processing unit 3 is automatically performed according to a predetermined arithmetic processing procedure.

The output unit 8 outputs the chart set by the chart setting unit 6, the index obtained by the index setting unit 7, and the time series data input by the input unit 2 and displays the data on a cathode ray tube or the like. 8a and a printer section 8b for printing this out.

The usage of the support device 1 will be described below. First, the time-series data input by the input unit 2 is time-series data based on existing teletext stock market conditions and the like, and these time-series data are, for example, predetermined hours such as hourly, daily, weekly or monthly. Automatically entered as a candlestick or a continuous line of gait. The input time-series data is processed by the center line calculation unit 4 of the processing unit 3 to form a center line made up of smoothed continuous lines by a cubic spline function calculation method for obtaining the center of fluctuating data. Is calculated. The center line finally output by this arithmetic processing automatically forms a flexible curve, for example, under the condition of the weight G given to the time series data X of the daily bar composed of the candle shown in FIG. A center line A is formed which is formed and has an extremely smooth curve with less vibration (curve shake or distortion). As described above, the arithmetic processing for setting the center line A is performed by converting the time-series data X into a common logarithmic value for calculation, and is converted into a natural value and displayed at the final output stage.

The input time-series data is subjected to the center line calculation processing, and then, in the upper and lower limit line calculation unit 5, based on the data of the center line A obtained by the center line calculation unit 4, the upper limit line B and the lower limit line are calculated. C and are set. The upper limit line B and the lower limit line C represent the probability of irregular fluctuation of the time-series data X as probability distribution lines in a predetermined range. It shows the limit of the rising and falling width. That is, the 5% upper limit line B indicates that there is a 5% probability that the time series data will be above the upper limit line B, and the 5% lower limit line C indicates that the time series data X is below the lower limit line C. The probability is 5%. The upper and lower limit lines B and C are calculated by common logarithmic values similarly to the calculation of the center line A, converted into natural values and output.
Therefore, the widths of the B and C lines are large at a high price and the widths of the B and C lines at a low price are small, but the deviation rate from the center line A is the same and the center line A is the same.
It is possible to form a smooth curve similar to, and to predict that the stock price will rise or fall roughly within the width of the upper and lower limit lines B and C. The upper and lower limit lines B and C are 1% to 95
Any% line such as% can be calculated, and one or more lines can be inserted as shown in FIG. The center line A and the upper and lower limit lines B, C are the center line and the upper and lower limit lines of the time series data related to the market transaction by the same arithmetic processing for all period units such as month, week, day and time. , It is possible to form the center line and upper and lower limit lines according to long-term, medium-term, and short-term investment policies, and it is easy to perform various calculations such as the first derivative and the second derivative. .

The center line A and the upper and lower limit lines B, which are processed by the center line calculation processing unit 4 and the upper and lower limit line calculation unit 5,
C is set in the chart setting unit 6 so as to be merged as a chart. As shown in FIG. 2, in the set chart, the center line A and the upper and lower limit lines B and C all show the flow of stock prices as a smooth curve, and when the stock price rises, the rising speed does not change rapidly. Even if there is, a smooth upward curve is always formed, and when turning downward, a smooth downward curve opposite to the case of rising is formed.

In the chart processed by the chart setting unit 6, the index setting unit 7 calculates an index for predicting a change in the stock price at a key point of a turning point of fluctuations in the stock price. At the points where investment efficiency is high among the turning points that change from falling to rising, the symbol “up” is added to the triangle mark indicating stock buying and its vicinity, and the specified turning point among the turning points that move from rising to falling. The part is set to display the inverted triangle mark and the character "Descent" in the vicinity thereof.

The curves A, B, C and the indexes are displayed on the display unit 8a and the printer unit 8 of the output unit 8.
It is displayed in b, and at that time, the time series numerical value X is also incorporated and displayed as a candlestick, and finally output as a chart as shown in FIG. Along with the output of the chart according to FIG. 2, the chart of FIG. 3 showing the rising and falling width of the center line separately calculated in the supporting device 1, the chart of FIG. By outputting the chart of FIG. 5 showing the changed hourly bar of the day and referring to these charts, the prediction of data and the transaction support according to FIG. 2 can be made more reliable.

The chart of FIG. 3 showing the rising and falling widths of the center line is a graph showing the difference between the natural value of the center line A and the previous value, and the center line is smooth. Because it is a curve, this chart also changes smoothly. The height of the bar graph in the plus area indicates the ascending speed of the center line, and similarly, the height in the minus area indicates the descending speed, whereby the tendency of the ups and downs of the time series data at that time point. And the width and speed can be known.

The chart of the current day bar in FIG.
The daily bar until the current time, the daily bar at the previous day, the center line, the upper and lower limit lines, and the movements of the next day after extrapolation and extension of these are graphed. The continuous line, the center line, and each upper and lower limit line of the transition of are drawn. The chart of the hourly bar on the same day in this figure may be drawn with a candlestick having a period unit of every 5 to 30 minutes.

An example of actual investment strategy and time series data prediction and transaction support as tactics based on each figure obtained by using such a support apparatus 1 will be described as follows. 1) In FIG. 2, when the center line A is facing downward and the index of “descent” is displayed, the rising / falling width of the center line in FIG. The numerical value of the lower limit line C indicates the statistical stochastic limit of the irregular fluctuation at that time. And from the past examples, the downward trend and the trend of the rate of decline and the rate of decline are estimated from this trend, which shows that there is a better buying place ahead, and that now we should refrain from buying. . 2) Next, when the center line A is facing upward and the index is displayed as “increase”, it is time to buy, and the center line and each %
See where the stock price at the current time is located on the upper and lower bounds of. Normally, it is located near the center line A where the upper and lower limit lines have a large%. However, the smaller the% of the lower limit line C and the lower the lower limit line C, the easier it is to buy. The higher the percentage of the upper limit B above A and the smaller the percentage, the more cautious the purchase should be. 3) In addition, in Fig. 2, when the index of increase in the stock you wish to buy appears and the due date elapses, you can also see the center line A and its upper and lower limit lines B, C, and the rise and fall range of the center line in Fig. 3. If the rate of increase or speed tends to increase with reference to the chart, the upper price still remains, so it is possible to easily judge the buying time by looking at the current day's bar or the hour's bar in the day, especially the lower limit. It turns out that a small percentage of the line is a great buying opportunity. It can be seen that buying should be cautious, as the upper and lower prices will naturally be small when the rise and fall widths and speeds of the centerline tend to reach a ceiling or decrease. 4) In the case of selling, consider the opposite of the case of buying. In this way, the chart makes it easy for you to make important judgments and trade executions on scientific and statistical grounds, such as buying, selling and waiting for the stock to wait for the next opportunity. And it can be done easily.

[0030]

EFFECT OF THE INVENTION The time series data prediction and transaction support device relating to the market transaction of the present invention inputs the time series data of the market transaction, statistically processes the input time series data,
These are output as a chart. With the output chart, it is possible to predict the decision material of the transaction based on scientific grounds and support the transaction. Then, it buys, sells, and waits (for example, waits for the next selling opportunity at the ceiling where the stocks bought are not sold and continue to show higher or lower prices), or to buy new ones. Do not abandon, wait for the next buying opportunity at the bottom price where there is a lower price or rising index, or consider other more favorable stock etc.) Can be easily and easily visually observed on the chart based on scientific and statistical grounds, and the final decision elements for individual time series data are only buying, selling and waiting. Also, it is possible to perform short selling (a transaction that usually starts with buying and ends with selling, but starts with reverse selling and ends with buying), which is said to be performed only by professionals.

The time-series data prediction and transaction support device relating to the market transaction of the present invention is used in various markets such as securities market including stock market, commodity market, foreign exchange market, financial market and futures market. It can be used for short-term forecasting and trading and option trading, and can be expected to have high hit rate and excellent efficiency.

[Brief description of drawings]

FIG. 1 is a block diagram showing each processing means of a time series data prediction and transaction support device relating to a market transaction of the present invention.

FIG. 2 is a diagram showing an example of a chart output by the prediction and transaction support device for time series data relating to the market transaction of the present invention.

FIG. 3 is a chart showing a rising and falling width of a center line corresponding to the chart of FIG.

FIG. 4 is a chart showing trading volume of stocks corresponding to the chart of FIG.

5 is a chart showing a part of the chart of FIG. 2 as a current day bar and a current day bar.

[Explanation of symbols]

1 Time Series Data Prediction and Trading Support Device for Market Trading 2 Input Unit 2a Data Capture Unit 2b Keyboard 3 Processing Unit 4 Centerline Calculation Unit 5 Upper and Lower Limit Line Calculation Unit 6 Chart Setting Unit 7 Index Setting Unit 8 Output Unit 8a Display section 8b Printer section A Center line B Upper limit line C Lower limit line X Time series data

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[Procedure amendment]

[Submission date] November 29, 1993

[Procedure Amendment 1]

[Document name to be amended] Statement

[Correction target item name] Full text

[Correction method] Change

[Correction content]

[Document name] Statement

Title: Prediction of time series data related to market transactions and transaction support device

[Claims]

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION This invention inputs time series data for trading and option trading in various markets such as securities markets including stock markets, commodity markets, foreign exchange markets, financial markets and futures trading markets. The present invention relates to an apparatus for predicting time series data relating to market transactions and a transaction support apparatus for accurately grasping the flow of prices and using them as guidelines for investment strategies and tactics.

[0002]

2. Description of the Related Art In the stock market and the like, various means are used as an index for expressing transactions in a time series, in which data is analyzed by a computer and various fluctuation factors and fluctuations are analyzed. Attempts have been made to use predictive devices that take account of this.

[0003]

However, in many of these prediction devices, the user inputs by his / her own judgment, and a method for making this judgment accurate is not incorporated. In addition, since the given time series data is used as it is for analysis or analysis, there is a drawback that it is not possible to accurately grasp the influence of fluctuations and sufficiently satisfy the prediction accuracy and efficiency. . For example, even if the buy instruction is successful, the sell instruction for it is too early and the price becomes 1.5 to 2 times higher after the sell instruction is issued, or the sell instruction is not issued in many cases. , Again, after the purchase instruction is issued 1
Since there are cases where it drops by 0% to 50%, most of the decisions had to be made taking into account the opinions of investment experts.

In view of the above circumstances, it is an object of the present invention to provide a time-series data forecasting and transaction support device relating to market transactions, which can be forecasted with a high degree of accuracy and efficiency. is there.

[0005]

In order to achieve the above-mentioned object, the time series data prediction and transaction support apparatus relating to the market transaction of the present invention comprises an input means for inputting the time series data of the market transaction and an input. A centerline calculating means for obtaining the center of fluctuation of the time series data as a centerline of a continuous smooth curve by spline function calculation, and irregular fluctuation of the time series data with respect to the centerline calculated by the centerline calculating means. Upper and lower limit line calculating means for obtaining the probability as a predetermined upper limit line and lower limit line, chart setting means for setting each calculated value of the center line and upper and lower limit lines in the chart, and calculating a required turning point of the set chart. Outputting the turning point calculation input means, the chart set by the chart setting means, and the turning point input by the turning point calculation input means, together with the time series data. It is characterized in that an output means that.

In the present invention, time-series data for predicting time-series data and inputting to the transaction support device for market transactions includes stock prices, securities prices and indexes , commodity prices, dollar quotes or futures prices and indexes. The individual time-series data, etc. picked up based on communication means such as teletext or personal computer communication or based on economic articles, etc. Alternatively, individual time series data can be manually input as appropriate using a keyboard or the like.

[0007] In the center line calculating means, the invention of Turkey determined as the center line of the smooth curve which is continuous the center of variation of time-series data input is employing a spline function calculations. Generally, in spline function calculation as a statistical method, odd-order calculations such as cubic spline function, quintic spline function and seventh-order spline function are known. This is not preferable because the vibration of the curve increases. In this spline function calculation, the required statistical weight G set by the weight calculation means is input and calculated.

In obtaining the probability of irregular fluctuation of time series data with respect to the center line obtained by the center line calculating means by the upper limit line and the lower limit line, the range of the upper limit line and the lower limit line is the time series with respect to the center line. The probability of irregular fluctuation of data can be set to a plurality of values such as 1% to 95%, but it is desirable to calculate as 5% among them.

The output means outputs the respective charts and the turning points together with a chart showing the rising and falling width of the center line, a chart showing the trading volume, and a chart showing the daily bar and the hourly bar in a predetermined period unit. It is desirable to be able to separately output one or more charts such as a chart showing details of time-series data. By referring to each of these charts, it is possible to more accurately grasp the flow of time-series data in a market transaction and make prediction and transaction support advantageous. The above output means
Although it is displayed on both the display and / or the printer, it is usually most preferable to use both the display and the printer.

When the time series data of the market transaction input to the transaction support apparatus of the present invention is provided as an analog amount, the time series data is input to the transaction support apparatus in advance or in the transaction support apparatus of the present invention. , And performs analog / digital conversion and inputs as a digital amount.

The respective calculation means such as the calculation of the weight G, the calculation of the upper and lower limit lines, and the calculation for setting the ascending index and the descending index as the turning points are based on the following specific methods.

1) Weight calculation means According to the investment policy of long-term, medium-term, and short-term, the time series data to be calculated is designated as either monthly, weekly, or daily, and the designated time series data is regularly paired. The value of the smoothed cubic spline function is calculated by converting the numerical value and inputting the initial value of the weight G. The first-order differential value, second-order differential value, and third-order differential value of this calculated value are calculated. Each derivative naturally forms a smooth curve with several waves varying from positive to negative. The weight G is changed and repeated calculation is performed until each differential value satisfies the set limit condition. Then, the value of the weight G when the limit condition is satisfied becomes the weight optimized according to the flow of the time-series data.

2) Means for calculating upper and lower limit lines In this case, the logarithmic value is also used for calculation in the same manner as described above, and the value is converted into a natural value and outputted. High and low prices of time series data and smoothed cubic spline function values (center line)
If you take the difference from and aggregate it, it will approximate a normal distribution curve, so
Calculate the standard deviation of this difference. In this calculation, the value 1.96 multiplied by the standard deviation at 50% on one side of the standard normal distribution table is 0.47500, that is, 47.5%. Therefore, the probability of taking a value of 1.96 or more multiplied by this standard deviation is 2.5%. Then, if 50% on one side of the standard normal distribution table is expanded to 100% and newly defined, the probability of taking a value of 1.96 or more of the value multiplied by the standard deviation is 5
%. Therefore, the center line + (standard deviation x 1.9)
The line 6) has a 5% probability of being higher than this line. In this way, each% line between 1% and 95% can be calculated, which allows the upper and lower limits to be calculated.

3) Calculation means for index of increase When a common logarithmic value of time series data is calculated several times by the exponential smoothing method, a smooth curve is obtained. This curve is linked to the smoothed cubic spline function value, the natural time series data, and the natural trading volume, and only when the set conditions are satisfied,
Output the index of rise.

4) Calculating means for the index of decline The common logarithmic value of the time series data is exponentially smoothed. Only when the condition set by linking the exponential smoothed value and the smoothed cubic spline function value is satisfied, the index of the descent is output.

In this way, by linking the rising and falling indices with the smoothed cubic spline function value and outputting them under the set conditions, only the merit of each value is output, and the maximum effect is obtained. It is something to demonstrate. In the calculation using the common logarithm, the base of the logarithm is 10, and even if the base is a base e of natural logarithm or a value of 2 to 100, the calculation effect is almost the same, but the calculation using the common logarithm is performed. preferable.

[0017]

In the time-series data prediction and transaction support device relating to the market transaction of the present invention, the time-series data for the market transaction is input by the input means, and the center of fluctuation of the input time-series data is calculated by the center line. Means for calculating a smoothed center line by means of spline function calculation, particularly cubic spline function calculation, and the upper and lower limit line calculation means for determining the probability of irregular fluctuation of the time series data with respect to the center line. Calculate the upper and lower limits of the range,
The center setting, the upper limit line and the lower limit line are calculated by the chart setting means so that the calculated values can be represented as a chart, and the required turning points of the set chart are calculated by the turning point operation input means. The chart set value and the turning point thus input can be output together with the time-series data by display means and / or printed out. Therefore, based on these output data, it is possible to accurately predict the flow of market transactions and accurately determine the timing of actions such as buying, selling, and waiting. At that time, together with the output of the chart and the turning point, the chart showing the footstep of the time series data in a predetermined period unit on a daily basis, an hourly basis, a chart showing the trading volume and a chart showing the range of rise and fall of the center line. Output one or more of them separately,
By referring to these, prediction of time series data and transaction support can be further enhanced.

[0018]

[Embodiment] Hereinafter, as an embodiment of a time series data prediction and transaction support device relating to a market transaction of the present invention, a time series data prediction and transaction support device relating to a stock market transaction will be cited with reference to the accompanying drawings. It will be specifically described. Figure 1
The time-series data prediction and transaction support device 1 (hereinafter, simply referred to as the support device 1 in this embodiment) related to market transactions shown in the block diagram of FIG. And a processing unit 3 for performing arithmetic processing on the input time-series data and setting it as predetermined data, and an output unit 8 for outputting the arithmetically processed data.

The input unit 2 receives the time-series data by character broadcasting, personal computer communication, or the like, or the time-series data for manual input as information, and inputs it as a data acquisition unit 2a.
And a keyboard 2b for operating the setting and instruction of the capture condition when inputting to the capturing unit 2a, the setting and instruction of the processing condition in the processing unit 3 and the output instruction of the display and the printer, and the time series data. When manually inputting, data may be input by operating the keyboard 2b.

The processing unit 3 includes a center line computing unit 4 for setting a center line of the irregular fluctuation of stock prices as a center line smoothed by spline function calculation based on the time series data input to the input unit 2. An upper / lower limit line calculation unit 5 for calculating and setting an upper limit line and a lower limit line with respect to the center line obtained by the center line calculation unit 4, and a chart setting unit for setting the center line and the upper / lower limit line as a band chart. 6 and an index setting unit 7 for calculating and setting a change prediction index at a turning point of the set flow fluctuation. Basically, each processing in the processing unit 3 is automatically performed according to a predetermined arithmetic processing procedure.

The output unit 8 outputs the chart set by the chart setting unit 6, the index obtained by the index setting unit 7, and the time series data input by the input unit 2 and displays the data on a cathode ray tube or the like. 8a and a printer section 8b for printing this out.

The usage of the support device 1 will be described below. First, the time-series data input by the input unit 2 is time-series data based on existing teletext stock market conditions and the like, and these time-series data are, for example, predetermined hours such as hourly, daily, weekly or monthly. Automatically entered as a candlestick or a continuous line of gait. The input time-series data is processed by the center line calculation unit 4 of the processing unit 3 to form a center line made up of smoothed continuous lines by a cubic spline function calculation method for obtaining the center of fluctuating data. Is calculated. The center line finally output by this arithmetic processing automatically forms a flexible curve, for example, under the condition of the weight G given to the time series data X of the daily bar composed of the candle shown in FIG. A center line A is formed which is formed and has an extremely smooth curve with less vibration (curve shake or distortion). As described above, the arithmetic processing for setting the center line A is performed by converting the time-series data X into a common logarithmic value for calculation, and is converted into a natural value and displayed at the final output stage.

The input time-series data is subjected to the center line calculation processing, and then, in the upper and lower limit line calculation unit 5, based on the data of the center line A obtained by the center line calculation unit 4, the upper limit line B and the lower limit line are calculated. C and are set. The upper limit line B and the lower limit line C represent the probability of irregular fluctuation of the time-series data X as probability distribution lines in a predetermined range. It shows the limit of the rising and falling width. That is, the 5% upper limit line B indicates that there is a 5% probability that the time series data will be above the upper limit line B, and the 5% lower limit line C indicates that the time series data X is below the lower limit line C. The probability is 5%. The upper and lower limit lines B and C are calculated by common logarithmic values similarly to the calculation of the center line A, converted into natural values and output.
Therefore, the widths of the B and C lines are large at a high price and the widths of the B and C lines at a low price are small, but the deviation rate from the center line A is the same and the center line A is the same.
It is possible to form a smooth curve similar to, and to predict that the stock price will rise or fall roughly within the width of the upper and lower limit lines B and C. The upper and lower limit lines B and C are 1% to 95
Any% line such as% can be calculated, and one or more lines can be inserted as shown in FIG. The center line A and the upper and lower limit lines B, C are the center line and the upper and lower limit lines of the time series data related to the market transaction by the same arithmetic processing for all period units such as month, week, day and time. , It is possible to form the center line and upper and lower limit lines according to long-term, medium-term, and short-term investment policies, and it is easy to perform various calculations such as the first derivative and the second derivative. .

The center line A and the upper and lower limit lines B, which are processed by the center line calculation processing unit 4 and the upper and lower limit line calculation unit 5,
C is set in the chart setting unit 6 so as to be merged as a chart. As shown in FIG. 2, in the set chart, the center line A and the upper and lower limit lines B and C all show the flow of stock prices as a smooth curve, and when the stock price rises, the rising speed does not change rapidly. Even if there is, a smooth upward curve is always formed, and when turning downward, a smooth downward curve opposite to the case of rising is formed.

[0025] The chart setting unit 6 in the treated chart, in the index setting portion 7, intended for calculating an index for predicting the change in the stock price of the flow at important turning point in the stock flow change, For example, of the turning points where the stock price changes from rising to rising, where the investment efficiency is high, the symbol "buying" is added to the triangular mark indicating buying of the stock and its vicinity, and the turning point It is set to display an inverted triangle mark and a character "Descent" in the vicinity thereof in a predetermined portion of the inside.

The curves A, B, C and the indexes are displayed on the display unit 8a and the printer unit 8 of the output unit 8.
2b, in which case the above-mentioned time series data X is also incorporated and displayed as a candlestick and finally shown in FIG.
It is output as a chart like. Along with the output of the chart according to FIG. 2, the chart of FIG. 3 showing the rising and falling width of the center line separately calculated in the supporting device 1, the chart of FIG. By outputting the chart of FIG. 5 showing the changed hourly bar of the day and referring to these charts, the prediction of data and the transaction support according to FIG. 2 can be made more reliable.

The chart of FIG. 3 showing the rising and falling widths of the center line is a graph showing the difference between the natural value of the center line A and the previous value, and the center line is smooth. Because it is a curve, this chart also changes smoothly. The height of the bar graph in the plus area indicates the ascending speed of the center line, and similarly, the height in the minus area indicates the descending speed, whereby the tendency of the ups and downs of the time series data at that time point. And the width and speed can be known.

The chart of the current day bar in FIG.
The daily bar until the current time, the daily bar at the previous day, the center line, the upper and lower limit lines, and the movements of the next day after extrapolation and extension of these are graphed. The continuous line, the center line, and each upper and lower limit line of the transition of are drawn. The chart of the hourly bar on the same day in this figure may be drawn with a candlestick having a period unit of every 5 to 30 minutes.

An example of actual investment strategy and time series data prediction and transaction support as tactics based on each figure obtained by using such a support apparatus 1 will be described as follows. 1) In FIG. 2, when the center line A is facing downward and the index of “descent” is displayed, the rising / falling width of the center line in FIG. The numerical value of the lower limit line C indicates the statistical stochastic limit of the irregular fluctuation at that time. And from the past examples, the downward trend and the trend of the rate of decline and the rate of decline are estimated from this trend, which shows that there is a better buying place ahead, and that now we should refrain from buying. . 2) Next, when the center line A is facing upward and the index is displayed as “increase”, it is time to buy, and the center line and each %
See where the stock price at the current time is located on the upper and lower bounds of. Is usually located at% a large upper and lower limit lines in the near with the center line indicates that may hit the hand of buying smaller the percent lower line under the center Sen以, center
You should be careful to buy the smaller the% upper limit line on Sen以. 3) In addition, in Fig. 2, when the index of increase in the stock you wish to buy appears and the due date elapses, you can also see the center line A and its upper and lower limit lines B, C, and the rise and fall range of the center line in Fig. 3. If the rate of increase or speed tends to increase with reference to the chart, the upper price still remains, so it is possible to easily judge the buying time by looking at the current day's bar or the hour's bar in the day, especially the lower limit. It turns out that a small percentage of the line is a great buying opportunity. It can be seen that buying should be cautious, as the upper and lower prices will naturally be small when the rise and fall widths and speeds of the centerline tend to reach a ceiling or decrease. 4) In the case of selling, consider the opposite of the case of buying. In this way, the chart makes it easy for you to make important judgments and trade executions on scientific and statistical grounds, such as buying, selling and waiting for the stock to wait for the next opportunity. And it can be done easily.

[0030]

EFFECT OF THE INVENTION The time series data prediction and transaction support device relating to the market transaction of the present invention inputs the time series data of the market transaction, statistically processes the input time series data,
These are output as a chart. With the output chart, it is possible to predict the decision material of the transaction based on scientific grounds and support the transaction. Then, it buys, sells, waits (for example, waits for the next opportunity to sell in the ceiling area where the stock bought is not sold but continues to show higher or lower prices), or new buys. Do not wait and wait for the next buying opportunity in the bottom price zone where the lower price or rising index appears, or consider other more favorable stock etc.) Can be easily and easily visually observed on the chart based on scientific and statistical grounds, and the final decision elements for individual time series data are only buying, selling and waiting. Also, it is possible to perform short selling (a transaction that usually starts with buying and ends with selling, but starts with reverse selling and ends with buying), which is said to be performed only by professionals.

The time-series data prediction and transaction support device relating to the market transaction of the present invention is used in various markets such as securities market including stock market, commodity market, foreign exchange market, financial market and futures market. It can be used for short-term forecasting and trading and option trading, and can be expected to have high hit rate and excellent efficiency.

[Brief description of drawings]

FIG. 1 is a block diagram showing each processing means of a time series data prediction and transaction support device relating to a market transaction of the present invention.

FIG. 2 is a diagram showing an example of a chart output by the prediction and transaction support device for time series data relating to the market transaction of the present invention.

FIG. 3 is a chart showing a rising and falling width of a center line corresponding to the chart of FIG.

FIG. 4 is a chart showing trading volume of stocks corresponding to the chart of FIG.

5 is a chart showing a part of the chart of FIG. 2 as a current day bar and a current day bar.

[Explanation of Codes] 1 Prediction and transaction support device for time series data related to market transactions 2 Input unit 2a Data acquisition unit 2b Keyboard 3 Processing unit 4 Center line calculation unit 5 Upper and lower limit line calculation unit 6 Chart setting unit 7 Index setting Part 8 Output part 8a Display display part 8b Printer part A Center line B Upper limit line C Lower limit line X Time series data

Claims (6)

[Claims] 1. Input means for inputting time-series data of market transactions, centerline calculation means for obtaining the center of fluctuation of the input time-series data as a centerline of a continuous smooth curve by spline function calculation, Upper and lower limit line calculating means for obtaining, as predetermined upper limit lines and lower limit lines, the probability of irregular fluctuation of time series data with respect to the center line calculated by the center line calculating means, and the calculated values of the center line and the upper and lower limit lines Is set in the chart, a turning point calculation input means for calculating and inputting a required turning point of the set chart, and a chart set by the chart setting means and the turning point calculation input means. A time-series data prediction and transaction support device relating to a market transaction, comprising a turning point and output means for outputting the time-series data together with the time-series data. 2. The spline function calculation is performed by setting optimized weights according to the flow of time-series data based on time series units such as month, week, and day. A time-series data prediction and transaction support device relating to a market transaction according to claim 1. 3. The time-series data prediction and transaction support device according to claim 1 or 2, wherein the spline function calculation is based on a smoothed cubic spline function calculation. 4. The time series relating to market transactions according to claim 1, wherein the upper and lower limit lines are calculated with the probability of irregular fluctuation of the time series data with respect to the center line being 5%, respectively. Data prediction and transaction support device. 5. The time-series data prediction and transaction support device according to claim 1, wherein the output means outputs by a display and / or a printer. 6. The time series data prediction and transaction support device according to claim 1, wherein the center line, the upper and lower limit lines, the turning point, and the time series data are output together with the rise and fall width of the center line. Time series data relating to a market transaction, characterized in that it is configured to separately output one or more selected from a chart, a chart showing a trading volume, and a chart showing details of time series data in a predetermined period unit. Prediction and transaction support device.