Analysis system and program for analyzing price variation of financial product

Abstract

To provide an analysis system and a program that can more easily provide accurate support information on the price variation of a financial product.SOLUTION: An analysis system for analyzing the price variation of a financial product acquires the daily price of the financial product, calculates, for each of a plurality of different price increase rates, the number of days required until the price of the financial product increases by the price increase rate on the basis of the daily price, calculates, for each of the price increase rates, the interest in a predetermined interest reference period on the basis of the number of days required, and outputs interest information for associating the interest for each of the price increase rates.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an analysis system and a program for analyzing price fluctuations of financial products. [Background technology]

[0002] In trading financial products, it is important to formulate an investment strategy taking into account past price fluctuations. For this reason, various systems that support trading based on price fluctuations are publicly known. For example, Patent Document 1 describes a technology that uses a neural network to generate advice based on past data on stock price increases and decreases. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-184131 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the conventional technology, there is a problem that it is difficult to provide accurate support information. For example, in Patent Document 1, machine learning is performed using a neural network, but in order to perform appropriate machine learning, it is necessary to appropriately design the neural network and prepare a large amount of appropriate teacher data, which is generally very difficult.

[0005] The present invention has been made to solve the above problems, and has an object to provide an analysis system and a program that can more easily provide accurate support information. [Means for solving the problem]

[0006] An example of an analysis system according to the present invention includes: An analysis system for analyzing price fluctuations of financial products, comprising: The analysis system comprises: Obtaining the daily price of said financial instrument; calculating the number of days required for the financial product to increase in price by a different rate of increase based on the daily price; For each of the price increase rates, calculate the yield within a predetermined yield base period based on the required number of days; Yield information relating the yield to each of the price appreciation rates is output.

[0007] Moreover, one example of the program according to the present invention causes a computer to operate as the above-mentioned analysis system. Effect of the Invention

[0008] The analysis system and program according to the present invention can more easily provide accurate yield information by analyzing price fluctuations of financial products. [Brief description of the drawings]

[0009] [Figure 1] 1 shows an example of the configuration of an analysis system according to a first embodiment of the present invention. [Diagram 2] An example of the format of price data handled by the analysis system in Figure 1. [Diagram 3] 2 is a flowchart showing the process flow of the analysis system of FIG. 1. [Figure 4] Specific examples of yield information. [Diagram 5] Another example of yield information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. [Embodiment 1] 1 shows an example of the configuration of an analysis system 10 according to the first embodiment of the present invention. The analysis system 10 is an analysis system that analyzes price fluctuations of financial products.

[0011] The analysis system 10 is configured using one or more computers. That is, the analysis system 10 has a hardware configuration as a known computer, and includes, for example, a calculation means 11 and a storage means 12. The calculation means 11 includes, for example, a processor, and the storage means 12 includes, for example, a storage medium such as a semiconductor memory device or a magnetic disk device.

[0012] The computer may also include input / output means, which may include, for example, input devices such as a keyboard and a mouse, output devices such as a display and a printer, and a communication device such as a network interface.

[0013] The storage means may store a program. The processor may execute the program, causing the computer to execute the functions described in the present embodiment. In other words, the program causes the computer to operate as the analysis system 10.

[0014] Fig. 2 shows an example of the format of price data handled by the analysis system 10. The price data 20 in Fig. 2 includes the daily prices of financial products. In the example in Fig. 2 and the following description, a specific stock is used as an example of a financial product, and in particular, the daily opening price is used as the stock price.

[0015] However, the price data may represent the prices of financial products other than stocks, or may represent the prices of a collection of multiple financial products (for example, TOPIX, Nikkei Stock Average, etc.). Furthermore, if the daily price is set as the opening price, it is preferable because it reflects news and the like from the closing time of the trading market to the opening time of the next day, but it is not limited to the opening price and may be, for example, the closing price, high price, low price, etc.

[0016] Price data 20 need not include prices for all days within a period; for example, data for days on which a trading market is closed may be omitted.

[0017] 3 is a flowchart showing the flow of processing in the analysis system 10. The operation of the analysis system 10 will be described below with reference to FIG.

[0018] 3, the analysis system 10 first acquires the opening price of a stock for each day (step S1). For example, the analysis system 10 accepts input of price data 20. The price data 20 may be stored in advance in the storage means 12, or may be input to the analysis system 10 via a portable storage device or a communication network.

[0019] Next, the analysis system 10 executes a loop process for the price increase rate. In the loop process, the analysis system 10 first determines the price increase rate in the loop (step S2). For example, the initial value is set to 1%, the final value is set to 100%, and the increment is set to 1%. That is, the first loop is set to 1%, the second loop is set to 2%, and the third loop is set to 3%. The initial value, final value, and increment of the loop can be designed as appropriate.

[0020] Next, the analysis system 10 calculates the number of days required for the stock to increase by the price increase rate in the loop based on the price data 20 (step S3).

[0021] As an example, we will explain the second loop (price increase rate of 2%) in detail. In the example in Figure 2, the stock price on the first day (January 4, 2016) is 23,456 yen. Since the price increase rate is 2%, we identify the first day on which the stock price will be 23,456 yen x 1.02 ≒ 23,925 yen or more, and calculate the number of days required until that day, starting from January 4, 2016.

[0022] Next, since the stock price on the second day (January 5, 2016) is 23,567 yen, we identify the first day on which the stock price will be 23,567 yen x 1.02 ≒ 24,038 yen or higher, and calculate the number of days until that day, starting from January 5, 2016.

[0023] Similarly, for all days (except the last day) included in the price data 20, the number of days required from that day is calculated. Then, the average number of days required from each day is calculated. This average number can be used as the number of days required corresponding to the rate of price increase. The average is calculated, for example, by the geometric mean, but it may also be calculated by the arithmetic mean, harmonic mean, logarithmic mean, etc.

[0024] In addition, if there is no price increase corresponding to the price increase rate in the loop starting from a certain day in the price data 20, the number of days required starting from that day is not calculated, and therefore the day is excluded from the calculation of the average value in step S3.

[0025] Also, if no price increase corresponding to the price increase rate in the loop has occurred on any day in the price data 20, the subsequent processing related to that price increase rate may be omitted. Alternatively, the number of days required for that price increase rate may be set to infinity, and the price may be treated as having no yield (0% yield).

[0026] The above is one example of a method for calculating the number of days required corresponding to the rate of price increase, but the specific calculation method is not limited to this and can be designed or modified as appropriate by a person skilled in the art.

[0027] Next, the analysis system 10 calculates the yield within a predetermined yield reference period for the price increase rate in the loop based on the number of days required calculated in step S3 (step S4). In this embodiment, this yield reference period is one year, but the yield reference period can be designed as long as it is a period of two days or more and less than the entire period of the price data 20.

[0028] For example, if the price increase rate is 2% and it takes 50 days, if you buy a stock and hold it for a year, the price will increase by 2% 365 / 50=7.3 times, so the price after one year will be 1.02 7.3 This is approximately 1.156 times, so the yield is approximately (1-1.156) x 100 = 15.6%.

[0029] After step S4, the analysis system 10 changes the price increase rate to the next value, and repeatedly executes the loop until the loop is completed for the final price increase rate (for example, 100%) (step S5).

[0030] To summarize the above loop processing, the analysis system 10 calculates the number of days required for a stock to increase in price by each of several different price increase rates based on the price data 20 (step S3 above), and then calculates the one-year yield for each price increase rate based on the number of days required (step S4 above).

[0031] After the loop process is completed, the analysis system 10 outputs yield information that associates a yield with each price increase rate (step S6).

[0032] A specific example of yield information is shown in Fig. 4. In the example of Fig. 4, yield information 31 is represented by a graph in which one axis (horizontal axis) represents the rate of price increase and the other axis (vertical axis) represents the yield (i.e., the magnitude of the ratio), but the representation format is not limited to this. The analysis system outputs such yield information. The output mode can be designed arbitrarily, and may be, for example, displayed by a display device, printed by a printer, transmitted via a communication network, or stored in a storage medium.

[0033] In this way, the analysis system 10 provides accurate yield information by analyzing stock price fluctuations. Users of the analysis system 10 can use this yield information as a reference when formulating investment strategies.

[0034] For example, in the example of FIG. 4, it is possible to identify the optimal price increase rate P that maximizes the one-year yield. In other words, after purchasing the stock of the issue, the user can most efficiently obtain profits by waiting until the price increases by P, and then selling it at that point. If the price increase rate is smaller than P, the investment efficiency will decrease because the price increase will not be sufficient, and if the price increase rate is larger than P, the price increase will take too long, and the investment efficiency will decrease.

[0035] Analysis system 10 may output information on the yield as well as information indicating the rate of price increase that maximizes the yield (for example, the value of P and the dashed line in the graph indicating its position).

[0036] In the example of Fig. 4, there is only one type of yield information, that is, the yield information is calculated based on a single yield reference period (e.g., the one-year period of 2016). If the price data includes information on multiple yield reference periods (e.g., price data for two or more years; the price data 20 in Fig. 2 includes data for seven years), the analysis system 10 can calculate and output the yield information for each yield reference period (i.e., for each year).

[0037] 5 shows a specific example of yield information in such a case. The analysis system 10 outputs, as the yield information, minimum yield information 41 corresponding to the year with the smallest yield (2018 in this example) among the seven years from 2016 to 2022, and maximum yield information 43 corresponding to the year with the largest yield (2022 in this example). The analysis system 10 may also output average yield information 42 indicating the average value of the yield information of all years.

[0038] The magnitude of the return for each year can be evaluated, for example, by integrating the return with respect to the rate of price increase (corresponding to the area of ​​the graph), but other calculation methods may also be used.

[0039] Such an output allows the user to formulate an investment strategy more flexibly. For example, when making an investment based on a pessimistic stock price forecast, the user can refer to the minimum return information 41, when making an investment based on an average stock price forecast, the user can refer to the average return information 42, and when making an investment based on an optimistic stock price forecast, the user can refer to the maximum return information 43.

[0040] Here, the price increase rate that maximizes the yield is generally different for the minimum yield information 41, the average yield information 42, and the maximum yield information 43. In the example of Fig. 5, the price increase rate that maximizes the yield in the minimum yield information 41 is the optimal price increase rate P1, the price increase rate that maximizes the yield in the average yield information 42 is the optimal price increase rate P2, and the price increase rate that maximizes the yield in the maximum yield information 43 is the optimal price increase rate P3.

[0041] The analysis system 10 may output information about each yield and may also output information representing the price increase rate that maximizes each yield (e.g., the values ​​of P1, P2, and P3, and / or dashed lines in the graph showing the positions of P1, P2, and P3, respectively).

[0042] In this way, the optimal price increase rate is output for each of the various conditions, so the user can refer to these. For example, if you want to maximize profits based on a pessimistic stock price forecast, you can buy the stock, wait until the price increases by P1, and then sell it. Similarly, if you want to maximize profits based on an average stock price forecast, you can wait until the price increases by P2, and if you want to maximize profits based on an optimistic stock price forecast, you can wait until the price increases by P3.

[0043] 5, only the yield information for the year with the minimum yield and the year with the maximum yield is output, and the yield information for other years is not output, but the analysis system 10 may output the yield information for other years (for example, all years). Furthermore, statistical values ​​other than the average value may be output for the yield information.

[0044] In the above-mentioned embodiment 1, only the price of a single financial product (a single stock) is handled, but it is more preferable to handle multiple financial products. In that case, the analysis system 10 may obtain price data for each financial product and output yield information for each financial product. In this way, the user can know the optimal price increase rate for each of multiple stocks, and can formulate an investment strategy optimized for each stock.

[0045] Those skilled in the art can arbitrarily add, change or delete components within the scope of the present invention in the above-described embodiment 1. For example, the analysis system 10 can be configured by multiple computers connected via a communication network. [Explanation of symbols]

[0046] 10. Analysis system 11...Arithmetic means 12...Memory means 20...Price data (daily prices) 31…Yield information 41…Minimum yield information 42…Average yield information 43…Maximum yield information P, P1, P2, P3…Optimal price increase rate

Claims

1. An analysis system for analyzing price fluctuations of financial products, comprising: The analysis system comprises: Obtaining the daily price of said financial instrument; calculating the number of days required for the financial product to increase in price by a different rate of increase based on the daily price; For each of the price increase rates, calculate the yield within a predetermined yield base period based on the required number of days; outputting yield information relating the yield to each of the price increase rates; Analysis system.

2. The analysis system of claim 1 , wherein the yield information is represented by a graph in which one axis represents the price increase rate and the other axis represents the yield.

3. The yield reference period is one year; said daily prices include daily prices for a period of two or more years; The analysis system comprises: Calculating the yield information on an annual basis; outputting average yield information obtained by averaging the yield information for all years; The analytical system of claim 1 .

4. The analysis system of claim 1 , wherein the financial instrument is a stock and the daily price is an opening price.

5. A program for causing a computer to operate as the analysis system according to any one of claims 1 to 4.

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