KR20140018531A - System for predicting price of stock - Google Patents

System for predicting price of stock Download PDF

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KR20140018531A
KR20140018531A KR1020120084731A KR20120084731A KR20140018531A KR 20140018531 A KR20140018531 A KR 20140018531A KR 1020120084731 A KR1020120084731 A KR 1020120084731A KR 20120084731 A KR20120084731 A KR 20120084731A KR 20140018531 A KR20140018531 A KR 20140018531A
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stock
price
expected
time point
client
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KR1020120084731A
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Korean (ko)
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박혜원
이기현
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케이티비투자증권 주식회사
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Priority to KR1020120084731A priority Critical patent/KR20140018531A/en
Publication of KR20140018531A publication Critical patent/KR20140018531A/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0281—Customer communication at a business location, e.g. providing product or service information, consulting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services

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Abstract

A stock prediction system is disclosed. The stock prediction system includes: an information delivery server which delivers information about a stock item to clients until a first time point; a predicted stock collecting server which receives a predicted stock signal which includes information about a predicted stock of the stock item in a second time point which is after the first time point from the clients; and an accuracy rate producing server which produces an accuracy rate of the clients by applying a weight value to a comparison result which compares an actual stock price of the stock item of the second time point with a predicted stock price, wherein the weight value can be determined by using at least one of actual stock price fluctuation ranges during a prediction period between the first time point and the second time point and during a predetermined period before the first time point. [Reference numerals] (120) Information delivery server; (130) Predicted stock collecting server; (140) Accuracy rate producing server; (150) Time point selecting server; (160) Relation setting server; (170_1,170_n) Client

Description

System for predicting price of stock}

The present invention relates to a stock price prediction system, and more particularly, to a stock price prediction system that can provide more reliable information by calculating a hit ratio by applying various weights in predicting a stock price after a certain period of time.

It is difficult for general users to analyze vast financial data to predict the direction of stock information. Therefore, target price forecasts have been provided by analysts of securities firms, which have superior advantages to individual investors in expertise, investment time, analysis methods, tools and information volume. For reference, there are various problems to use for real securities investment.

There is also a risk of judging stocks based on a person's predicted information. It is common for securities firms to give conflicting opinions, in which case it is difficult for general investors to set criteria for the choice of which opinions to trust, and in the case of such information, it is a matter of trusting the person. It is very difficult to set standards. In the end, too much information is a stumbling block to making rational and economic decisions.

The problem to be solved by the present invention is to calculate the hit ratio of the client by applying a variety of weights so that investors can refer to the expected price provided by the plurality of clients and the expected price provided by the client with a high hit rate can provide a variety of related information Stock price prediction system.

The stock price prediction system according to an embodiment of the present invention for achieving the above object is an information delivery server for transmitting information on the stock items up to the first time point to the client, a second time point after the first time point A weighted to a predicted price collection server that receives an estimated stock price signal including information about the expected stock price of the stock item from the client, and a comparison result of comparing the actual stock price and the expected stock price of the stock item at the second time point. A hit rate calculation server configured to calculate a hit rate of the client by applying a value, wherein the weight is at least one of an expected period between the first time point and the second time point and a change in the actual price during a predetermined period before the first time point. Can be determined using.

The hit ratio calculation server applies the weight differently for each section corresponding to the expected period so that the weight increases as the expected period increases, and the section corresponding to the change in the actual price increases so that the weight increases as the actual price fluctuation increases. The weight may be applied differently.

The stock price prediction system further includes a viewpoint selection server that receives a viewpoint selection signal including information on a second viewpoint selected from the client among a plurality of second viewpoints provided to the clients, wherein the expected stock acquisition server Provides the client with the maximum value and the minimum value of the expected stock price of the stock item at the selected second time point, and the estimated price of the stock item at the selected second time point within the range of the maximum value and the minimum value. Receiving an expected stock signal including information about the client from the client, and the hit ratio calculation server applies the weight to a comparison result of comparing the actual stock price of the stock item at the selected second time point with the expected stock price of the client; The hit ratio can be calculated.

The hit rate calculation server may calculate the hit rate for each stock item by averaging hit rates of the clients for each of the stock items.

The expected price collection server may calculate the total average value of the estimated price values using the estimated price signals received from the clients and register the average price.

The expected price collection server may use the expected price signals received from the clients to increase the average price of the stock price higher than the actual price of the stock price at the first time point and the stock price at the first time point. The average price of the stock price lower than the actual price of the average price can be calculated and registered on the corresponding web page.

The first time point may be a current time point or a time after the end of the previous day's stock market, and the second time point may be a time point that is one day, one week, one month or three months from the first time point.

The estimated price collection server calculates at least one of a first average value of average price estimates of clients whose hit rate is greater than or equal to a threshold value, and a second average value averaged estimated price values of clients whose hit rate is less than the threshold value and corresponds to a corresponding web page. You can register at

The expected price signal includes the client's opinion on the reason for predicting the expected stock price of the stock item, and the expected price collection server may register the client's opinion on the corresponding web page.

The stock price prediction system includes a relationship setting server for establishing a following relationship between a second client or the stock item and the first client in response to a following request signal received from a first client among the clients, The information delivery server may include information on the estimated stock price received from the second client, information on an expected stock price of the stock item in which the following relationship is established, a hit ratio of the second client, and a stock item in which the following relationship is established. At least one of average hit ratios of the clients may be transmitted to the first client.

The stock price prediction system according to an embodiment of the inventive concept may refer to the direction and expected stock price of a stock item based on group information including a plurality of clients rather than one opinion, thereby increasing or increasing a corresponding stock item. There are advantages that can help predict the direction of the decline. In addition, the stock price prediction system according to an embodiment of the inventive concept selects a more reliable prediction result when investors refer to stock investment by calculating a hit ratio by applying different weights according to the predictable difficulty. There is an advantage to getting a standard to do this.

BRIEF DESCRIPTION OF THE DRAWINGS A brief description of each drawing is provided to more fully understand the drawings recited in the description of the invention.
1 is a block diagram of a stock price prediction system according to an embodiment of the inventive concept.
FIG. 2 is a flowchart of a stock price prediction method using the stock price prediction system of FIG. 1.
3 to 6 illustrate web pages related to the stock price prediction system 100 of FIG. 1.
7 is a diagram illustrating an embodiment of a following relationship.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the practice of the present invention, reference should be made to the accompanying drawings and the accompanying drawings which illustrate preferred embodiments of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, the present invention will be described in detail with reference to the preferred embodiments of the present invention with reference to the accompanying drawings. Like reference symbols in the drawings denote like elements.

1 is a block diagram of a stock price prediction system 100 according to an embodiment of the inventive concept, and FIG. 2 is a flowchart of a stock price prediction method using the stock price prediction system 100 of FIG. 1. 3 to 6 are diagrams illustrating web pages related to the stock price prediction system 100 of FIG. 1, and FIG. 7 is a diagram illustrating an embodiment of a following relationship.

1 to 7, the stock price prediction system 100 may include a server 110 that communicates with a plurality of clients 170_1,..., 170_n (n is a natural number). The server 110 may include an information delivery server 120, an expected price collection server 130, a hit rate calculation server 150, a time point selection server 150, and a relationship setting server 160.

When the clients 170_1,..., 170_n register the corresponding websites and log in and select a predetermined stock item, the information delivery server 120 selects the stock items. 170_n), information about the stock item up to the first time point may be transmitted (S210). The information on the stock item may include a chart, full-day closing price, market price, high price, low price, trading volume, trading value, etc., as shown in FIG. It is not. The first time point may be a current time point or may be a time point after the end of the stock market the day before. For example, when the first time point is the current time point, the information delivery server 120 may transmit information on the stock item up to the current time point.

Hereinafter, for convenience of description, communication between the client 170_1 and the server 110 will be described. Each of the remaining clients may also communicate with the server 110 as described below.

The client 170_1 refers to the information on the stock items up to the first time point received from the information delivery server 120, and includes an information on the expected stock price of the stock items at the second time point. It may be transmitted to the server 110, and the expected price collection server 130 may receive the expected price signal (S220). The estimated stock signal may include at least one of information on the estimated stock price and information predicting whether the stock price rises or falls. The second time point may be a time point after the first time point, and may be, for example, one day, one week, one month, or three months after the first time point. However, the present invention is not limited to this case and the second time point may be various other time points.

The second time point may be one time point selected by the client 170_1 among a plurality of second time points provided by the time point selection server 150, or the client 170_1 may not be provided with the second time points. The second time point may be set directly. For example, when the time point selection server 150 provides the client 170_1 with second time points as a point in time after one day, one week, one month, and three months, based on the first time point, the client 170_1 May select one of the second viewpoints and the viewpoint selection server 150 may receive a viewpoint selection signal including information on the selected second viewpoint from the client 170_1. A case in which the time point selection server 150 provides the second time points is shown in FIG. 3, and one week later (February 2) and one week later, assuming that the first time point is February 1, 1 It allows you to choose between months and three months later.

The estimated price collection server 130 may provide the client 170_1 with a maximum value and a minimum value of the expected stock price of the stock item based on a second time point selected by the client 170_1. The maximum value of the expected price is a share price when the stock item continues to record an upper limit until the second time point based on the first time point, and the minimum value of the expected price is up to the second time point based on the first time point. The stock price may be a case where the stock price continues to record a lower limit. The client 170_1 provided with the maximum value and the minimum value of the expected stock price may select an expected stock price of the stock item within the range between the maximum value and the minimum value, and the expected price signal is a range between the maximum value and the minimum value. It may include information on the expected stock price of the selected stock item.

Referring to FIG. 4, since the client 170_1 pre-selected that the stock price will rise on February 2, which is one day later, the target price is shown in a case where the target price can be entered within the range of the stock price that is increased from 0% to 15% from the current price. Doing. As such, the stock price may be selected first after the rise or fall of the stock item, and the forecast price may include only a rise or fall.

The expected stock price signal may include an opinion of the client 170_1 regarding the reason for the expected stock price of the stock item. As shown in FIG. 4, the comment input field may be displayed to allow the client 170_1 to select one of the plurality of fixed phrases or the client 170_1 may directly input his / her opinion.

The hit ratio calculation server 140 may calculate a hit ratio of the client 170_1 by applying a weight to a comparison result of comparing the actual stock price and the expected stock price of the stock item at the second time point (S230). The weight may be determined using at least one of an expected period between the first time point and the second time point and a change in the actual price during a predetermined period before the first time point. For example, the hit ratio calculation server 140 applies the weight differently for each section corresponding to the expected period so that the weight increases as the estimated period increases, and the actual price increases so that the weight increases as the actual price fluctuation range increases. The weight may be differently applied to each section corresponding to the variation range.

The longer the forecast period is, the more difficult it is to predict the expected price, and the larger the actual price fluctuation is, the more difficult it is to predict the expected price. For example, if the estimated period is within 1 day, a weight of 0.5 is applied, if the estimated period is within 1 week, a weight of 0.7 is applied, and if the estimated period is within 1 month, a weight of 0.8 is applied. If the estimated period is within three months, a weight of 1 may be applied to apply a different hit rate according to the period even if the estimated price is the same as the actual price at the second time point. As another example, a weight of 0.5 is applied when the stock price of the stock is fluctuating within 1%, and a weight of 0.6 is applied when the stock price of the stock is fluctuating within 3%. When the stock price of the stock price has changed within 5%, the hit ratio may be calculated by applying a weighting factor of 0.7.

The hit ratio calculation server 140 may calculate hit ratios for the stock items by averaging hit ratios of the clients for each of the stock items. For example, if the average hit ratio of clients for Samsung Electronics is 40% and the average hit ratio of clients for LG Electronics is 70%, the clients are more credible than the expected price of clients for LG Electronics. You can judge that. For example, FIG. 5 illustrates a case where the average hit ratio of clients for the stock item is 83%.

The estimated price collection server 130 may calculate the total average value of the estimated price values using the estimated price signals received from the clients 170_1,..., 170_n and register the corresponding average price on the corresponding web page. For example, FIG. 5 illustrates a case in which the average value of the client's expected stock prices for the stock items is $ 967,000. In addition, the expected price collection server 130 calculates at least one of a first average value of average expected stock prices of clients whose hit ratio is greater than or equal to a threshold value and a second average value of average estimated prices of clients whose hit ratio is less than the threshold value. You can register on the corresponding web page. For example, when the threshold is 70%, the average of the expected stock prices of clients having the hit ratio of 70% or more is the first average value and the average of the expected stock prices of clients having the hit ratio less than 70% is the first value. 2 is the average value. The overall average value, the first average value, or the second average value may be expressed in various forms such as a numeric form and a graph form on a web page.

In addition, the expected price collection server 130 uses the expected price signals received from the clients to obtain an average price of the stock price higher than the actual price of the stock item at the first point in time and the first time point. The average price of the stock price lower than the actual price of the stock price may be calculated and registered on the web page. For example, FIG. 6 illustrates a case in which the rising average value and the decreasing average value of February 13, 14, 15, 16, and 17, respectively, are displayed together in an actual share price chart. However, the present invention is not limited to this case, and the rising average value and the falling average value may be registered in the web page in various forms.

The relationship setting server 160 may establish a following relationship between the second client or the stock item and the first client in response to the following request signal received from the first client. The first client following the stock item or the second client means that the first client wants to be provided with content related to the stock item or the second client. The content related to the stock item may include news related to the stock item, articles related to the stock item (eg, articles written in connection with the stock item by experts or the general public), and the like. The content related to the client may include a post registered by the client, a web page linked by the client, a ripple on a post registered by the client, and the like.

For example, it is assumed that the first client 710 follows the second client 730 and the first stock item 720 as shown in FIG. 7. In this case, the information delivery server 120 may provide information on the expected stock price received from the second client 730, information on the stock price 720 of the first stock item 720 in which the following relationship is established, and the second client. At least one of the hit ratio 730 and the average hit ratio of the clients for the first stock item 720 with the following relationship may be transmitted to the first client 710. That is, information calculated or provided by the stock price prediction system 100 in relation to the second client 730 or the first stock item 720 in the following relationship may be automatically delivered to the first client 710. have.

As described above, an optimal embodiment has been disclosed in the drawings and specification. Although specific terms have been employed herein, they are used for purposes of illustration only and are not intended to limit the scope of the invention as defined in the claims or the claims. Therefore, those skilled in the art will appreciate that various modifications and equivalent embodiments are possible without departing from the scope of the present invention. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

100: stock price prediction system 110: server
120: information delivery server 130: expected price collection server
140: hit rate calculation server 150: time point selection server
160: relationship setting server 170_1 to 170_n: client

Claims (10)

An information delivery server for transmitting information on stock items up to the first time point to clients;
An expected stock acquisition server that receives an expected stock price signal from the client, the estimated stock price signal including information about an estimated stock price of the stock item at a second time point after the first time point; And
A hit ratio calculation server configured to calculate a hit ratio of the client by applying a weight to a comparison result of comparing the actual stock price and the expected stock price of the stock item at the second time point,
The weighting value,
The stock price prediction system of claim 1, wherein the price is determined using at least one of an expected period between the first time point and the second time point and a change in the actual price during a predetermined period before the first time point. The method of claim 1, wherein the hit ratio calculation server,
The weight is differently applied to each section corresponding to the expected period so that the weight is larger as the expected period is longer, and the weight is differently applied to each section corresponding to the variation of the actual price so that the weight is larger as the actual price is larger. Stock price prediction system, characterized in that. The method of claim 1, wherein the expected price collection server,
And a viewpoint selection server for receiving a viewpoint selection signal including information on a second viewpoint selected from the client among a plurality of second viewpoints provided to the clients,
The estimated price collection server,
Provide the client with a maximum value and a minimum value of the expected stock price of the stock item at the selected second time point, and compare the expected price of the stock item with the selected second time point within the range of the maximum value and the minimum value. Receiving an expected stock signal including information from the client,
The hit ratio calculation server,
And a hit ratio of the client is calculated by applying the weight to a comparison result of comparing the actual stock price of the stock item with the expected stock price at the second selected time point. The method of claim 1, wherein the hit ratio calculation server,
The stock price prediction system, characterized by calculating the hit ratio for each stock item by averaging the hit ratios of the clients for each of the stock items. The method of claim 1, wherein the expected price collection server,
And using the expected price signals received from the clients, calculate a total average value of the expected price values and register the average value in the corresponding web page. The method of claim 1, wherein the expected price collection server,
By using the expected stock signals received from the clients, a rising average value of average stock prices higher than the actual stock price of the stock item at the first point in time and an expected stock price lower than the actual stock price of the stock item at the first point in time Stock price prediction system, characterized in that the average of the falling average value to calculate the registration on the corresponding web page. The method of claim 1, wherein the first time point is
At the present time or after the close of the previous day's stock market,
The second time point,
The stock price prediction system, characterized in that the first time, one week, one month or three months have elapsed from the first time point. The method of claim 1, wherein the expected price collection server,
Calculating and registering at least one of a first average value of average expected stock prices of clients whose hit rate is greater than or equal to a threshold value and a second average value averaged expected stock prices of clients whose hit rate is less than the threshold value and registering the same in a corresponding web page; Stock price prediction system. The method of claim 1, wherein the expected price signal,
The client's opinion on why the stock price is expected;
The estimated price collection server,
And a client's opinion is registered in a corresponding web page. According to claim 1, wherein the stock price prediction system,
A relationship setting server configured to establish a following relationship between a second client or the stock item and the first client in response to a following request signal received from a first client of the clients,
The information delivery server,
Information on the expected price received from the second client, information on the expected stock price of the stock item for which the following relationship is established, the hit ratio of the second client, and the average hit ratio of the clients for the stock item with the following relationship; Delivering at least one of to the first client.
KR1020120084731A 2012-08-02 2012-08-02 System for predicting price of stock KR20140018531A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20200016609A (en) * 2018-08-07 2020-02-17 김재현 General Purpose Prediction System
KR20210139032A (en) 2020-05-13 2021-11-22 김동훈 Apparatus and method for providing fair price of a stock using target price of securities reports

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20200016609A (en) * 2018-08-07 2020-02-17 김재현 General Purpose Prediction System
KR20210139032A (en) 2020-05-13 2021-11-22 김동훈 Apparatus and method for providing fair price of a stock using target price of securities reports

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