TW201928843A - Analysis method and system for predicting next day's rising and falling probability using historical trajectory of K-line chart from three consecutive days focusing on the information of the K-line chart from three consecutive days instead of a single K-line chart - Google Patents

Abstract

The present invention provides an analysis system and an analysis method for predicting the next day's rising and falling probability using the historical trajectory of the K-line chart from three consecutive days. The analysis system comprising: a capturing module, a comparison module, a sorting module and a statistical module. The analysis system and the analysis method use the historical trajectory of the K-line chart from three consecutive days to obtain by comparison the degree of approximation by scientific calculation and then perform classification and compile statistics based on the degree of approximation to predict the rising and falling probability for the next day. In this way, scientific statistical methods and actual data can be used to provide investors with more accurate analysis results which focus on the information of the K-line chart from three consecutive days instead of a single K-line chart. Thus, the comparison of approximation degree has higher reliability, achieving the purpose of improving the accuracy of the analysis results.

Description

Analytical method and system for predicting the probability of rising and falling every other day by using the historical trajectory of the continuous three-day K-line chart

The present invention belongs to the field of stock market analysis, and in particular relates to an analytical method and system for predicting the probability of an increase in the next day through a scientific method to utilize the historical trajectory of the continuous three-day K-line chart.

According to the current era of information development, "financial management" has become more and more frequent in people's lives. Especially with the advancement of network technology, everyone can quickly obtain all the financial and financial information needed, and stock investment. It is a common financial management method for people. In general, in the process of investing in stocks, investors often focus on what stocks to buy, and when to decide when to buy or sell, so many investors have learned how to enter the market, and After the game, it began to study the indicators and news of various investments. The most common indicator for investors to pay attention to and analyze and judge is the K-line chart. However, since the traditional way of analyzing K-line charts is based on the accumulated experience of people's past investment, each person has his own set of analysis methods. Because of his own subjective analysis, investors may not be able to get stocks. Profit from investment.

Therefore, for the convenience of investors, some people have inferred a set of observation methods for a single-day K-line chart or a composite K-line chart based on years of experience and subjective opinions. Please refer to FIGS. 1A and 1B, which are schematic diagrams of a conventional single K-line type and a composite K-line type. As shown in the figure, each K-line pattern has some predecessors summed up the possibility. Follow-up trend, although able Investors integrate data, but because there are too many ways of summing up, investors still need to compare various aspects and find relevant information in judgment, which is very inconvenient. So now there are a lot of investment analysis systems that help investors to compare, such as the technical content mentioned in the Republic of China No. I488138 patent, which can help investors quickly compare the aspects of this inductive method. And inform the investor about the analysis information of the searched situation, so that the investor can make subsequent investment judgments. However, if the current investor's line graph is not consistent with any of the inductive methods, the system cannot advise investors or must look for similar patterns. Relevant investment advice, this will cause investors to get the wrong information, and then make a wrong judgment. Moreover, because the inductive method used by the system is based on the accumulation of experience and the derivation of subjective opinions, the lack of detailed statistical data or theoretical support leads to the inductive way of memorizing and helping the investors. The whole information, but there is not enough reliability in the investment direction.

In view of this, the inventor feels that he has not perfected his mind and painstakingly studied it, and based on his accumulated experience in the industry for many years, he provides a historical trajectory using the three-day K-line chart to predict the next day's ups and downs. The analysis method and system are intended to improve the lack of the above-mentioned prior art.

Accordingly, it is an object of the present invention to provide an analysis method and system for predicting the probability of an increase in the next day using the historical trajectory of the K-line chart for three consecutive days, and using scientific statistical methods and actual data to further present investors. Accurate analysis of results, and focus on the information of the K-line chart for three consecutive days instead of a single K-line chart, in order to analyze the statistical process, to achieve the purpose of improving the accuracy of the analysis results.

In order to achieve the above object, the present invention utilizes a historical trajectory of a continuous three-day K-line chart to predict an analysis method of the next day's rate of increase, and the method includes: extracting a three-day K-line chart information of a forecasting stock, the three-day K The line graph information has a plurality of first eigenvalues; each of the historical trajectories has a plurality of second eigenvalues compared to the degree of similarity between the three-day K-line graph information and the complex historical trajectory; wherein the comparison manner is The first eigenvalues are respectively calculated with the second eigenvalues of each of the historical trajectories to obtain a complex approximation; the historical trajectories are arranged, and the values are arranged in a small to large manner according to the values of the approximations. And select the historical trajectories of the first 60~100 strokes; and count the ups and downs of each of the selected historical trajectories on the next day, and predict the rise and fall probability of the three-day K-line chart information on the next day according to the statistical results; Among them, these historical trajectories are the three-day K-line chart historical information of the stock trading market.

Moreover, the present invention provides an analysis system that utilizes a historical trajectory of a three-day K-line chart to predict an alternate rate of increase in the next day, and includes: a capture module for extracting one of the predicted shares for three days K-line diagram information, the three-day K-line diagram information system has a plurality of first eigenvalues; a comparison module, which is provided with a degree of similarity to the three-day K-line diagram information and the complex historical trajectory, each Each of the historical trajectories has a plurality of second eigenvalues; wherein the aligning manner is that the first eigenvalues are respectively calculated with the second eigenvalues of each of the historical trajectories and a complex approximation is obtained, and the manner The historical track is the three-day K-line chart historical information of each stock of the stock exchange market; an array module is arranged to arrange the historical tracks, and is arranged in a small to large manner according to the values of the approximations. And select the historical trajectories of the first 60~100 strokes; and a statistical module, which is used to count the ups and downs of each of the selected historical trajectories on the next day, and predict the three-day K-line according to the statistical results. The rate of increase and decrease of the information on the next day.

Based on the above method and device, "in comparison with the three-day K-line map information and In the step of the degree of similarity of the plural historical trajectories or in the comparison module, the historical trajectories that are compared are only the three-day K-line map historical information of the predicted stock calendar, so that the predicted The rate of change is more in line with the company's performance over the years, improving accuracy.

Preferably, the first feature value and the second feature value of each of the historical tracks include an opening price, a highest price, a lowest price, a closing price of the first day, and an opening price of the second day. Price, lowest price, closing price and opening price, highest price, lowest price, closing price of the third day. Moreover, the detailed comparison method is to divide the opening price, the highest price and the lowest price of the first day, the second day and the third day of the first characteristic value by the closing price of the corresponding day, and the second The closing price of the day and the third day is divided by the closing price of the first day to obtain 11 first calculus values; and the first day, the second day, and the second eigenvalue of each of the historical trajectories are further The opening price, the highest price and the lowest price of the three days are respectively divided by the closing price of the day of the match, and the closing price of the second day and the third day are respectively divided by the closing price of the first day to obtain 11 second calculated values; Then, the first calculated values are subtracted from the corresponding second calculated values to obtain 11 third calculated values, and then the third calculated values are respectively squared and added to obtain one of them. The approximation. In this way, the more similar data can be searched for statistics through scientific calculation.

Preferably, when the probability of the forecasting stock is greater than or equal to 70%, the forecasting stock is recommended to allow the investor to make subsequent trading judgments.

In this way, the present invention makes the approximation degree by scientifically calculating the historical information of the K-line chart for three consecutive days of the past year, and the comparison method is approximated by scientific calculation, so that the analysis method and system have detailed The data support, in turn, provides investors with clearer and more detailed analysis results and prediction probabilities.

1‧‧‧Analysis system

11‧‧‧Capture module

12‧‧‧ Alignment module

13‧‧‧ Arrangement module

14‧‧‧Statistical Module

15‧‧‧Recommended module

S001~S005‧‧‧Steps

Figure 1A is a schematic diagram of a single-day K-line.

Figure 1B is a schematic diagram of a conventional K-line.

Figure 2 is a flow chart of a preferred embodiment of the present invention.

Figure 3 is a block diagram of a preferred embodiment of the present invention.

In the following description, the same components are denoted by the same reference numerals for the sake of understanding.

Please refer to FIG. 2 and FIG. 3, which are flowcharts and block diagrams of a preferred embodiment of the present invention. As shown in the figure, in the present embodiment, the present invention provides an analysis system 1 that utilizes a historical trajectory of a continuous three-day K-line chart to predict the rate of increase in the next day, which includes: a capture module 11, a ratio The module 12, an array module 13, a statistical module 14, and a recommendation module 15 are provided.

The system and method technology of the present invention are inseparable from each other, so the operation and interconnection relationship between the two will be described below. The analysis method used by the analysis system 1 includes: capturing, by the capture module 11, a three-day K-line map information of a predicted stock (step S001), wherein the three-day K-line map information has a plural number The first feature value, and in the embodiment, the first feature value includes the opening price, the highest price, the lowest price, the closing price of the first day, the opening price, the highest price, the lowest price, and the closing of the second day. The price and the opening price, the highest price, the lowest price, and the closing price of the third day. Then, the comparison module 12 compares the similarity between the three-day K-line diagram information and the complex historical trajectory (step S002), and in this embodiment, each of the historical trajectories has a plurality of second eigenvalues. And the second characteristic value includes the opening price, the highest price, the lowest price, the closing price of the first day, the opening price, the highest price, the lowest price, the closing price, and the opening price of the third day of the second day, Highest price, lowest price, closing price.

Among them, the method of comparison is as follows. First, the opening, the highest price, and the lowest price of the first, second, and third days of the first characteristic value are respectively divided by the closing price of the corresponding day, and the closing of the second and third days is performed. The price is divided by the closing price of the first day to get 11 first calculated values. And dividing the opening price, the highest price and the lowest price of the first, second and third days of the second characteristic value of the historical track by the closing price of the corresponding day, and the second day And the closing price of the third day is divided by the closing price of the first day to obtain 11 second calculus values. The first calculated values and the second calculated values are as shown in Table 1 below:

Where t is the first day, t+1 is the second day, t+2 is the third day, C and C ^' represent the closing price, H and H ^' represent the highest price, L and L ^' represent the lowest price, O and O ^' represents the opening price.

Then, the first calculated values are subtracted from the corresponding second calculated values to obtain 11 third calculated values, that is, the corresponding fields in the respective numbers in Table 1 are subtracted to obtain the same The three arithmetic values are then squared and then summed to obtain the approximation of the degree of similarity between the historical trajectory and the three-day K-line graph information. And repeating the above comparison method until the The historical trajectories are all completed.

Then, after the comparison is completed, the traversing module 13 arranges the historical trajectories in a small to large manner according to the values of the approximation values, and selects the historical trajectories of the first 60 to 100 pens (step S003). In this embodiment, the preferred ones select 75 such historical trajectories, so that the computing resources and the accuracy are balanced, so as to ensure the accuracy of the prediction, and not excessively occupy the resources required for the calculation. After selecting these historical trajectories, the statistical module 14 counts the rise and fall results of each selected historical trajectory every other day, and predicts the probability of the next day's rise and fall of the three-day K-line chart information according to the statistical result (steps) S004), for example, the statistical result is that 50 such historical trajectories have risen on the next day, and 25 such historical trajectories have fallen on the next day, the probability is 50/75=66.67%, and the probability of rising is marked as And when some historical trajectories appear in a flat state on the next day, the statistics are up.

In addition, these historical trajectories are the three-day K-line map historical information of the stock trading market, so that the number of samples available for comparison increases, and the overall accuracy rate is improved, but the historical trajectory can also be only the prediction. The historical information of the K-line chart of the third day of the stock year, so that the predicted rate of change is more consistent with the performance of the company over the years, and the accuracy of the individual is improved, so it is not limited to this. Finally, in this embodiment, when the probability of the rise and fall of the predicted stock is greater than or equal to 70%, the recommended stock is recommended by the recommendation module 15 (step S005), so that the analysis system 1 can be used. The investor has a clear and predictive basis for the analysis.

In summary, through the analysis method and analysis system 1 provided by the present invention, scientific statistical methods and detailed data can be used to corroborate and actually propose the predicted rate of rise and fall, instead of viewing the single-day K-line as traditionally used. Or a composite K-line and then make a general and vague judgment based on the trend of others' induction, their own experience or subjective consciousness, and then make the investors more clear and Detailed analysis results and prediction probability. Moreover, by focusing the search and comparison information on the information of the K-line chart for three consecutive days instead of the single K-line chart, the reliability is higher when the similarity is compared, thereby improving the accuracy of the prediction probability. The effect.

However, the above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the practice of the present invention, so that it is common knowledge in the art or equivalent or easy to be familiar with the technology. Variations and modifications made by those skilled in the art without departing from the spirit and scope of the invention are intended to be included within the scope of the invention.

Claims (10)

An analysis method for using the historical trajectory of a continuous three-day K-line chart to predict the probability of a rise and fall of the next day, the method comprising: extracting a three-day K-line chart information of a predicted stock, the three-day K-line chart information system having a plurality of a first eigenvalue; each of the historical trajectories has a plurality of second eigenvalues compared to the degree of similarity between the three-day K-line graph information and the complex historical trajectory; wherein the comparing manner is the first eigenvalues respectively Calculating the second eigenvalues of each of the historical trajectories and obtaining a complex approximation; arranging the historical trajectories, and arranging according to the values of the approximations in a small to large manner, and selecting the first 60 to 100 pens The historical trajectories; and the results of the ups and downs of each of the selected historical trajectories on the next day, and predicting the rise and fall probability of the three-day K-line chart information on the next day according to the statistical results; wherein the historical trajectories are For the three-day K-line chart historical information of the stock exchange market. For example, in the analysis method described in claim 1, wherein in the step of "similarity to the three-day K-line map information and the complex historical trajectory", the historical trajectories that are compared are only Forecast the K-line chart history information of the stock calendar for three days. The analysis method of claim 2, wherein the first feature value and the second feature value of each of the historical tracks comprise an opening price, a highest price, a lowest price, and Closing price, opening price, highest price, lowest price, closing price and opening price, highest price, lowest price, closing price of the third day on the second day. For example, the analysis method described in claim 3, wherein the detailed comparison method is The opening price, the highest price and the lowest price of the first, second and third days of the first characteristic value are respectively divided by the closing price of the corresponding day, and the closing prices of the second day and the third day are respectively divided Obtaining 11 first calculated values at the closing price of the first day; and opening, highest, and lowest of the first, second, and third days of the second characteristic values of each of the historical trajectories The price is divided by the closing price of the day of the match, and the closing price of the second day and the third day are respectively divided by the closing price of the first day to obtain 11 second calculated values; then, the first calculated value is Corresponding to the second calculated values, the two third calculated values are obtained by subtracting the two calculated values, and then the third calculated values are respectively squared and added to obtain one of the approximate values. For example, the analysis method described in claim 4, wherein the forecasting stock is recommended when the probability of the forecasting stock is greater than or equal to 70%. An analysis system that utilizes a historical trajectory of a three-day K-line chart to predict an alternate rate of increase in the next day, and includes: a capture module for extracting a three-day K-line chart information of a predicted stock, the third The daily K-line diagram information has a plurality of first eigenvalues; a comparison module is provided with a degree of similarity to the three-day K-line diagram information and the complex historical trajectory, each of the historical trajectories having a plurality of a second eigenvalue; wherein the aligning manner is that the first eigenvalues are respectively calculated with the second eigenvalues of each of the historical trajectories and a complex approximation is obtained, and the historical trajectories are stock exchange markets K-line chart history information of each stock for the past three years; an array module, which is arranged to arrange the historical trajectories, and arranged according to the values of the approximations in a small to large manner, and selects the first 60~100 pens Such historical trajectories; and a statistical module for counting the rise and fall of each of the historical trajectories selected every other day According to the results of the statistics, the probability of the next day's rise and fall of the three-day K-line chart information is predicted. The analysis system of claim 6, wherein the comparison module compares only the three-day K-line map history information of the predicted stocks in the historical trajectories. The analysis system of claim 7, wherein the first feature value and the second feature value of each of the historical tracks comprise an opening price, a highest price, and a lowest price of the first day. Closing price, opening price, highest price, lowest price, closing price and opening price, highest price, lowest price, closing price of the third day on the second day. The analysis system of claim 8, wherein the detailed comparison method is an opening price, a highest price, and a lowest price of the first, second, and third days of the first characteristic value. Dividing by the closing price of the day of the match, and dividing the closing price of the second day and the third day by the closing price of the first day respectively, obtaining 11 first calculated values; and then each of the historical trajectories The opening price, the highest price and the lowest price of the first day, the second day and the third day of the second eigenvalue are respectively divided by the closing price of the day of the match, and the closing price of the second day and the third day are respectively divided by the first 11 second calculus values are obtained from the closing price of the day; then, the first calculus values are subtracted from the corresponding second calculus values to obtain 11 third calculus values, and then the same The three arithmetic values are squared and added to obtain one of the approximations. For example, the analysis system described in claim 9 further includes a recommendation module for recommending the forecasting stock when the probability of the forecasting stock is greater than or equal to 70%.