Stock price prediction system and stock price prediction program

Abstract

We provide a stock price prediction system and program that accurately grasps trends in stock price fluctuations. [Solution] The stock price prediction system 10 comprises a reference value setting unit 11 that obtains the closing stock price on a reference date for the company to be predicted and sets the stock price as the reference value; a stock price acquisition unit 12 that obtains the company's daily closing stock price over a specified period as daily stock prices and stores them in a recording DB 16; a fluctuation rate calculation unit 13 that calculates the fluctuation rate between the reference value and the daily stock price stored in the recording DB and records this as a daily fluctuation rate in a storage DB 17; and a trend analysis unit 14 that analyzes the trend of the company's stock price based on the daily fluctuation rate recorded in the storage DB. The trend analysis unit uses the daily fluctuation rate recorded in the storage DB to perform an enthalpy transformation as a linear function of the daily fluctuation rate value on an arbitrarily selected day during the specified period and the daily fluctuation rate value on the current day, thereby showing the trend of the company's stock price as a line.

Description

[Technical Field]

[0001] The present invention relates to a stock price prediction system and a stock price prediction program for predicting a company's stock price. [Background technology]

[0002] Stock price prediction devices that predict daily fluctuating stock prices have been known for some time. For example, Patent Document 1 discloses a "time series data prediction method" that identifies and predicts highly nonlinear time series data by solving a nonlinear differential equation that represents a main variable and an auxiliary variable, and identifying the main variable.

[0003] The "Time Series Data Prediction Method" in Patent Document 1 mentions that it is particularly useful for predicting highly nonlinear time series data, particularly time series data in the securities and finance fields, such as stock prices and exchange rates, and in the distribution field, such as demand for consumer goods. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 11-296501 Summary of the Invention [Problem to be solved by the invention]

[0005] An object of the present invention is to provide a stock price prediction system that can grasp trends in stock price fluctuations with high accuracy by analyzing the rate of fluctuation from the stock price reference value in a time series. [Means for solving the problem]

[0006] In order to achieve the above object, the stock price prediction system according to the first invention comprises: A stock price prediction system that predicts a company's stock price, a reference value setting unit that acquires the closing stock price on a reference date for a company to be predicted and sets the stock price as a reference value; a stock price acquisition unit that acquires the daily closing stock prices of the company for a predetermined period as daily stock prices and stores them in a record DB; a fluctuation rate calculation unit that calculates the fluctuation rate between the reference value and the daily stock price stored in the record DB and records the calculated fluctuation rate in the storage DB as a daily fluctuation rate; Based on the daily fluctuation rate recorded in the storage DB, Using enthalpy conversion, a trend analysis unit that analyzes the trend of the company's stock price during a period to be predicted; Equipped with The aforementioned The enthalpy conversion in the trend analysis section is Using a chart with "days" on the horizontal axis and "daily fluctuation rate" on the vertical axis, In the chart, a straight line connecting the daily fluctuation rate X1 of the previous day and the daily fluctuation rate Y of the current day is derived as a linear function Y1, and In the chart, the daily fluctuation rate Xn of n (n≧2) days prior, arbitrarily selected within the predetermined period, is translated onto the vertical line representing the daily fluctuation rate X1 of the previous day, and a straight line connecting the translated daily fluctuation rate Xn and the daily fluctuation rate Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. It is characterized by:

[0007] The stock price prediction program according to the second invention is A program for predicting a company's stock price, which is installed on a computer. a reference value setting step of acquiring the closing stock price on a reference date for the company to be predicted and setting the stock price as the reference value; a stock price acquisition step of acquiring the daily closing stock prices of the company for a predetermined period as daily stock prices and storing them in a record DB; a fluctuation rate calculation step of calculating a fluctuation rate between the reference value and the daily stock price stored in the record DB and recording the calculated fluctuation rate in the storage DB as a daily fluctuation rate; Based on the daily fluctuation rate recorded in the storage DB, Using enthalpy conversion, a trend analysis step of analyzing the trend of the company's stock price during a period to be predicted; and The aforementioned The enthalpy conversion in the trend analysis step is Using a chart with "days" on the horizontal axis and "daily fluctuation rate" on the vertical axis, In the chart, a straight line connecting the daily fluctuation rate X1 of the previous day and the daily fluctuation rate Y of the current day is derived as a linear function Y1, and In the chart, the daily fluctuation rate Xn of n (n≧2) days prior, arbitrarily selected within the predetermined period, is translated onto the vertical line representing the daily fluctuation rate X1 of the previous day, and a straight line connecting the translated daily fluctuation rate Xn and the daily fluctuation rate Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. It is characterized by:

[0008] The stock price prediction system according to the third invention is A stock price prediction system that predicts a company's stock price, A stock price acquisition unit that acquires daily closing stock prices for a company to be predicted over a predetermined period as daily stock prices and stores them in a record DB; Based on the daily stock price recorded in the record DB, Using enthalpy conversion, a trend analysis unit that analyzes the trend of the company's stock price during a period to be predicted; Equipped with The aforementioned The enthalpy conversion in the trend analysis section is Using a chart with "days" on the horizontal axis and "daily stock price" on the vertical axis, In the chart, a straight line connecting the daily stock price X1 of the previous day and the daily stock price Y of the current day is derived as a linear function Y1, and In the chart, the daily stock price Xn from n (n≧2) days ago, arbitrarily selected within the predetermined period, is translated onto a vertical line representing the daily stock price X1 of the previous day, and a straight line connecting the translated daily stock price Xn and the daily stock price Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. It is characterized by:

[0009] A stock price prediction program according to a fourth aspect of the present invention is A program for predicting a company's stock price, which is installed on a computer. a stock price acquisition step of acquiring daily closing stock prices of a company to be predicted over a predetermined period as daily stock prices and storing them in a record DB; Based on the daily stock price recorded in the record DB, Using enthalpy conversion, a trend analysis step of analyzing the trend of the company's stock price during a period to be predicted; and The aforementioned The enthalpy conversion in the trend analysis step is Using a chart with "days" on the horizontal axis and "daily stock price" on the vertical axis, In the chart, a straight line connecting the daily stock price X1 of the previous day and the daily stock price Y of the current day is derived as a linear function Y1, and In the chart, the daily stock price Xn from n (n≧2) days ago, arbitrarily selected within the predetermined period, is translated onto a vertical line representing the daily stock price X1 of the previous day, and a straight line connecting the translated daily stock price Xn and the daily stock price Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. It is characterized by: [Effects of the Invention]

[0010] According to the present invention, by analyzing the fluctuation rate from the stock price reference value over time for the prices of companies whose prices fluctuate in the trading market, it is possible to grasp trends in stock price fluctuations with high accuracy, and it is expected that the accuracy of predictions of future trends will be improved. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a functional configuration diagram showing the functional configuration of a stock price prediction system according to an embodiment of the present invention. [Figure 2] 1 is a flowchart showing the overall processing procedure in a stock price prediction system according to an embodiment of the present invention. [Figure 3] FIG. 1 is a schematic diagram showing an example of enthalpy conversion in a stock price prediction system according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0012] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings. However, the present invention is not limited to the following embodiments.

[0013] Fig. 1 is a functional configuration diagram showing the functional configuration of a stock price prediction system according to an embodiment of the present invention. As shown in Fig. 1, a stock price prediction system 10 includes a base value setting unit 11, a stock price acquisition unit 12, a fluctuation rate calculation unit 13, and a trend analysis unit 14, and is configured to analyze the trend of a company's stock price and calculate a prediction trend by analyzing the fluctuation rate from the base stock price of the company to be predicted over time.

[0014] Here, the stock price prediction system 10 is a general computer device, and includes, for example, a processing unit (CPU), a main memory device (RAM), an auxiliary memory device such as a HDD, SSD, or flash memory, an input device such as a keyboard, mouse, or touch panel, an output device such as a display or speaker, a communication device for communicating with external devices, etc. Furthermore, a smartphone, a tablet terminal, a PC (Personal Computer), etc. can be used as the computer device.

[0015] The reference value setting unit 11 acquires the closing stock price of a company to be predicted on a reference date, and sets the stock price as the reference value.

[0016] Here, the above-mentioned "companies to be predicted" can be configured so that information on one or more companies (e.g., companies A and B) to be predicted is set in advance. Alternatively, the information on one or more companies (e.g., companies A and B) can be input and set from an input device at the appropriate time in response to an instruction from an operator.

[0017] The "reference date" may be configured so that information on a past date that serves as the basis for analysis is set in advance, or may be configured so that information on a past date that serves as the basis is input and set from an input device at the appropriate time in response to an instruction from an operator.

[0018] Furthermore, as a means for acquiring the closing stock price of the company on the "base date," for example, the system may be configured to acquire information on the target stock price by linking with another system via a communication network, or the system may be configured so that the information on the target stock price is input and set from an input device in response to an operator's instruction.

[0019] The stock price acquisition unit 12 acquires the closing stock prices for each day in a predetermined period for the companies set by the reference value setting unit 11 as daily stock prices, and stores them in the record DB 16. That is, the record DB 16 stores the daily stock prices for each company that is the target of prediction.

[0020] The "predetermined period" may be configured such that the date information of the past period to be analyzed is set in advance, or alternatively, the date information of the past period to be analyzed as a reference may be input and set from an input device at the appropriate time in response to an instruction from an operator.

[0021] Furthermore, as a means for obtaining the daily closing stock prices during the "predetermined period" as daily stock prices, the system may be configured to obtain information on target stock prices by linking with another system via a communication network, for example. Alternatively, the system may be configured so that information on target stock prices is input and obtained from an input device in response to an operator's instruction.

[0022] Fluctuation rate calculation unit 13 calculates the volatility between the reference value and the daily stock price (closing stock price for each day during a predetermined period) stored in record DB 16 for the company to be predicted, and records it as a daily volatility in storage DB 17. That is, in storage DB 17, the daily volatility for each company to be predicted is recorded as time-series data.

[0023] Fluctuation rate calculation unit 13 can also be configured to set comparison dates for multiple points in the period up to the current day, including 50 days prior, calculate the variability between the reference value and the daily stock price on the comparison date stored in record DB 16, and record this as a daily variability in storage DB 17. In other words, when calculating the daily variability, it can also be configured to use the daily stock prices on comparison dates for multiple points in a predetermined period, rather than using all daily stock prices in a predetermined period.

[0024] The trend analysis unit 14 analyzes the trend of the company's stock price during the period to be predicted based on the daily fluctuation rate recorded in the storage DB 17.

[0025] Here, the "period to be predicted" may be configured so that information on the period to be predicted is set in advance, or may be configured so that information on the period to be predicted is input and set from an input device in response to an instruction from an operator at an appropriate time.

[0026] Furthermore, when analyzing the trend of the company's stock price, the trend analysis unit 14 can be configured to use the daily fluctuation rate recorded in the storage DB 17 to perform an enthalpy transformation as a linear function of the value of the daily fluctuation rate on an arbitrarily selected day during the specified period and the value of the daily fluctuation rate on the current day, thereby showing the trend of the company's stock price as a line.

[0027] In addition to the configuration described above, the trend analysis unit 14 may be configured to analyze the trend of the company's stock price during the period to be predicted, based on the daily stock prices recorded in the record DB 16. In this case, the trend analysis unit 14 can be configured to use the daily stock prices recorded in the record DB 16 to perform enthalpy transformation as a linear function of the daily stock price value on a day arbitrarily selected during the predetermined period and the daily stock price value on the current day, when analyzing the trend of the company's stock price, so as to display the trend of the company's stock price as a line.

[0028] Next, the process executed by this system will be described with reference to the flowchart shown in Fig. 2. Fig. 2 is a flowchart showing the overall processing procedure in the stock price prediction system according to the embodiment of the present invention.

[0029] <Step S11> For a company to be predicted, the closing stock price of the company on the base date is obtained and set as the base price.

[0030] <Step S12> For a company to be predicted, the closing stock price for each day during a predetermined period is obtained as a daily stock price and stored in the record DB 16. That is, the record DB 16 stores the daily stock price for each company to be predicted.

[0031] <Step S13> For the company to be predicted, the fluctuation rate between the reference value set in step S11 and the daily stock price (closing stock price for each day during a predetermined period) stored in the record DB 16 is calculated and recorded as a daily fluctuation rate in the storage DB 17. That is, the daily fluctuation rate for each company to be predicted is recorded as time-series data in the storage DB 17.

[0032] Furthermore, when calculating the daily fluctuation rate, instead of using all daily stock prices in a predetermined period, it is also possible to use daily stock prices on comparison dates at multiple points in the predetermined period. That is, when calculating the daily fluctuation rate, comparison dates at multiple points can be set for the period up to the current day, including 50 days prior, and the fluctuation rate between the reference value and the daily stock price on the comparison date stored in record DB 16 can be calculated and recorded in storage DB 17 as the daily fluctuation rate.

[0033] <Step S14> The trend of the company's stock price during the period to be predicted is analyzed and a predicted value is calculated based on the daily fluctuation rate recorded in storage DB 17. Specifically, when analyzing the trend of the company's stock price, the daily fluctuation rate recorded in storage DB 17 is used to perform enthalpy transformation as a linear function of the value of the daily fluctuation rate on an arbitrarily selected day during the predetermined period and the value of the daily fluctuation rate on the current day, thereby showing the trend of the company's stock price as a line.

[0034] Next, we will explain the procedure for calculating predicted values ​​using the enthalpy transformation. As shown in Figure 3, from continuous volatility or stock price values, a line drawn between the current price and the previous day's price and arbitrarily selected past values ​​(e.g., 5 days ago, 10 days ago, 25 days ago, 50 days ago) are transferred onto the vertical line of the previous day's price. The line drawn between the transferred point and the current price is used to predict future trends based on the angle of the line and whether it is rising or falling. The tangent y is derived from the equation y = ax + b. For example, if all lines connecting past values ​​are on an upward trend and have an acute angle, and the line connecting the current price and the previous day's price shows an obtuse downward trend, this is information that indicates a sell price. Similarly, if all lines connecting past values ​​are on a downward trend and have an acute angle, and the line connecting the current price and the previous day's price shows an obtuse upward trend, this is information that indicates a buy price.

[0035] Furthermore, for the volatility rate or stock price, multiple comparison dates (for example, 50 days ago, 25 days ago, 10 days ago, 5 days ago) are set, and using the previous day's value as the base, the current day's value and arbitrarily selected past values ​​(for example, 5 days ago, 10 days ago, 25 days ago, 50 days ago) are shifted onto a vertical line of the previous day's value, and the shifted points are compared with the current day's value, and a line is drawn showing the trend from the past to the present, thereby providing information for predicting future trends through enthalpy transformation.

[0036] By executing the above data processing procedure (steps S11 to S14), it becomes possible to analyze the fluctuation rate from the stock price reference value for the company being predicted in time series, and furthermore, to grasp the trend of stock price fluctuations with high accuracy.

[0037] The above data processing procedure (steps S11 to S14) may be realized as a method executed by a computer, or may be realized as a program to be executed by a computer.

[0038] Furthermore, in the above data processing procedure (steps S11 to S14), stock prices may be used instead of the fluctuation rate. That is, the trend in stock prices is used instead of the trend in fluctuation rate. Compared to the fluctuation rate, the amount of change is not amplified, so the angle of the line drawn by the enthalpy conversion becomes obtuse, but it can still be used as a prediction method.

[0039] As described above, according to the stock price prediction system of the present invention, by analyzing the prices of companies whose prices fluctuate in the trading market using enthalpy transformation and the daily fluctuation rate (or daily stock price) from the stock price benchmark value, it is possible to grasp trends in stock price fluctuations with high accuracy, and it is expected that the accuracy of predictions of future trends will be further improved. [Explanation of symbols]

[0040] 11...Reference value setting section 12...Stock Price Acquisition Department 13...Fluctuation rate calculation section 14…Trend analysis department 16...Record DB 17…Storage DB

Claims

1. A stock price prediction system that predicts a company's stock price, a reference value setting unit that acquires the closing stock price on a reference date for a company to be predicted and sets the stock price as a reference value; a stock price acquisition unit that acquires the daily closing stock prices of the company for a predetermined period as daily stock prices and stores them in a record DB; a fluctuation rate calculation unit that calculates the fluctuation rate between the reference value and the daily stock price stored in the record DB and records the calculated fluctuation rate in the storage DB as a daily fluctuation rate; a trend analysis unit that analyzes the trend of the company's stock price during a period to be predicted using enthalpy transformation based on the daily fluctuation rate recorded in the storage DB; Equipped with The enthalpy conversion in the trend analysis unit is Using a chart with "days" on the horizontal axis and "daily fluctuation rate" on the vertical axis, In the chart, a straight line connecting the daily fluctuation rate X1 of the previous day and the daily fluctuation rate Y of the current day is derived as a linear function Y1, and In the chart, the daily fluctuation rate Xn of n (n≧2) days prior, arbitrarily selected within the predetermined period, is translated onto the vertical line representing the daily fluctuation rate X1 of the previous day, and a straight line connecting the translated daily fluctuation rate Xn and the daily fluctuation rate Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. A stock price prediction system characterized by:

2. A program for predicting a company's stock price, which is installed on a computer. a reference value setting step of acquiring the closing stock price on a reference date for the company to be predicted and setting the stock price as the reference value; a stock price acquisition step of acquiring the daily closing stock prices of the company for a predetermined period as daily stock prices and storing them in a record DB; a fluctuation rate calculation step of calculating a fluctuation rate between the reference value and the daily stock price stored in the record DB and recording the calculated fluctuation rate in the storage DB as a daily fluctuation rate; a trend analysis step of analyzing the trend of the company's stock price during a period to be predicted using enthalpy transformation based on the daily fluctuation rate recorded in the storage DB; and The enthalpy conversion in the trend analysis step is Using a chart with "days" on the horizontal axis and "daily fluctuation rate" on the vertical axis, In the chart, a straight line connecting the daily fluctuation rate X1 of the previous day and the daily fluctuation rate Y of the current day is derived as a linear function Y1, and In the chart, the daily fluctuation rate Xn of n (n≧2) days prior, arbitrarily selected within the predetermined period, is translated onto the vertical line representing the daily fluctuation rate X1 of the previous day, and a straight line connecting the translated daily fluctuation rate Xn and the daily fluctuation rate Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. A stock price prediction program characterized by:

3. A stock price prediction system that predicts a company's stock price, A stock price acquisition unit that acquires daily closing stock prices for a company to be predicted over a predetermined period as daily stock prices and stores them in a record DB; a trend analysis unit that analyzes the trend of the company's stock price during a period to be predicted using enthalpy transformation based on the daily stock price recorded in the record DB; Equipped with The enthalpy conversion in the trend analysis unit is Using a chart with "days" on the horizontal axis and "daily stock price" on the vertical axis, In the chart, a straight line connecting the daily stock price X1 of the previous day and the daily stock price Y of the current day is derived as a linear function Y1, and In the chart, the daily stock price Xn from n (n≧2) days ago, arbitrarily selected within the predetermined period, is translated onto the vertical line representing the daily stock price X1 of the previous day, and a straight line connecting the translated daily stock price Xn and the daily stock price Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. A stock price prediction system characterized by:

4. A program for predicting a company's stock price, which is installed on a computer. a stock price acquisition step of acquiring daily closing stock prices of a company to be predicted over a predetermined period as daily stock prices and storing them in a record DB; a trend analysis step of analyzing the trend of the company's stock price during a period to be predicted using enthalpy transformation based on the daily stock price recorded in the record DB; and The enthalpy conversion in the trend analysis step is Using a chart with "days" on the horizontal axis and "daily stock price" on the vertical axis, In the chart, a straight line connecting the daily stock price X1 of the previous day and the daily stock price Y of the current day is derived as a linear function Y1, and In the chart, the daily stock price Xn from n (n≧2) days ago, arbitrarily selected within the predetermined period, is translated onto the vertical line representing the daily stock price X1 of the previous day, and a straight line connecting the translated daily stock price Xn and the daily stock price Y of the current day is derived as a linear function Yn; Analyze the slope of the linear function Y1 and the slopes of multiple linear functions Yn to present information about the trend of stock price fluctuations. A stock price prediction program characterized by:

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