CN111882434A - Intelligent stock screening and evaluating method - Google Patents
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Abstract
The invention discloses an intelligent stock screening and evaluating method, which comprises the following steps of S1: establishing a fund model, downloading and collecting K-line data of stocks in real time and establishing a database; step S2: and selecting K-line data in a plurality of recent periods from the database, searching each data point in the plurality of periods, and judging whether the highest point is generated in the latest period so as to judge whether to enter the stock library. The intelligent stock screening and evaluating method disclosed by the invention has the advantages that the parameter selection is special, the data analysis is rapid, the timeliness is strong, and the information corresponding to the stock tendency in a daily fluctuation state can be met; the method also has a real-time reminding function, the data is downloaded in real time, the database is refreshed in real time, asset objects meeting the model standards are screened, and scores are extracted according to parameter values.
Description
Technical Field
The invention belongs to the technical field of stock screening and evaluation, and particularly relates to an intelligent stock screening and evaluation method.
Background
With the improvement of living standard of people, the investment concept of people is gradually enhanced, more and more people begin to pay attention to the stock market and the fund market, and the attention degree is higher and higher. The existing stock software not only provides stock quotation information for users, but also provides relevant information of stocks, stock evaluation information, enterprise consultation, news and the like for the users. However, the existing online stock-consulting system has too general test points and hysteresis, and cannot comprehensively describe the stock trend state in the day.
The publication number is: CN106056449A entitled an invention patent of stock information push system and method, the technical proposal discloses that the management server (1) comprises a database (100), a data receiving module (101) communicated with the database (100), a stock information element setting module (102), a data calculating module (103), a user behavior obtaining module (104), an information processing module (105), a stock screening module (106) and an active push module (107); the data receiving module (101) is used for receiving a plurality of stock information issued by the enterprise server in real time and storing the stock information in the database (100); the stock information element setting module (102) is used for presetting condition elements for evaluating a stock concern value, and respectively endowing the condition elements with the weight ratio occupied in the evaluation stock concern value, each condition element at least comprises two specific factors, the stock information element setting module (102) is also used for respectively endowing score values for the specific factors and storing the score values in the database (100), and the condition elements comprise stock codes, stock name similarity, market value change trend, market value size, daily volume of trade, financial data, high-level manager history condition, stockholder in-and-out change condition and capital score red; the data calculation module (103) is used for calculating the attention values of a plurality of stocks stored in the database (100) according to the weighted average of the weight ratio of the condition elements stored in the database (100) and the score value of the specific factor, and storing the attention values in the database (100); the user behavior acquisition module (104) is used for acquiring stock information of individual stocks clicked by a user and sending the stock information to the information processing module (105); the information processing module (105) is used for screening out condition elements from the received stock information, calculating the attention value X of each stock according to the weight ratio of the condition elements stored in the database (100) and the weighted average of the score values of the specific factors, and sending the attention value X to the stock screening module (106); the stock screening module (106) screens out individual stocks with an interest value range of X +/-M in the database (100) according to the interest value X calculated by the information processing module (105), and sends stock information corresponding to the individual stocks to the active pushing module (107), wherein M is a numerical value preset in the database (100) for screening the individual stocks ".
Taking the above patent as an example, although the invention discloses the stock information screening, the technical scheme is different from that of the invention. Therefore, the above problems can be further improved.
Disclosure of Invention
The invention mainly aims to provide an intelligent stock screening and evaluating method which is special in parameter selection, rapid in data analysis and strong in timeliness and can meet information corresponding to stock trends in a daily fluctuation state; the method also has a real-time reminding function, the data is downloaded in real time, the database is refreshed in real time, asset objects meeting the model standards are screened, and scores are extracted according to parameter values.
The invention also aims to provide an intelligent stock screening and evaluating method which has the advantages of accurate scoring, strong pertinence, high efficiency and the like.
In order to achieve the above purpose, the invention provides an intelligent stock screening and evaluating method, which is used for meeting information corresponding to stock tendency in a daily fluctuation state, and comprises the following steps:
step S1: setting a fund model, downloading and collecting K-line data (including the highest price, the lowest price, the closing price, the volume of bargaining and the like of the stock in unit time) of the stock in real time and establishing a database;
step S2: selecting K-line data in a plurality of recent periods (including previous continuous periods of a latest period, which can be selected according to the requirements of a user) from a database, retrieving each data point (the data point comprises a highest point, a next place, a lowest point and the like) in the plurality of periods, and judging whether the highest point is generated in the latest period so as to judge whether to enter a stock library;
step S3: rejecting stock marks with unqualified investment style in a stock library according to the basic surface information to form a suitable alternative library (go to ST and go to market withdrawal);
step S4: a scoring system is set up by selecting each parameter (the parameters comprise 1. whether the parameter is in an alternative library, 2.A price, C price distance, 3.E time, 4. price in a tray, 5. price for opening a tray, 6. transaction amount, 7.a time, 8.C time, 9.d time, 10.E time, 11.B-C parameter, 12. not in a tray, 13. current stock price, 14.F time, 15.En price-current price, 16.H percent and the like)
Step S5: continuously screening real-time updated data in the database by the fund model according to a target screening mode meeting the asset targets, and extracting scores according to parameters (the scores can be continuously refreshed and changed along with the change of transaction time);
step S6: real-time reminders for individual stocks (pages of asset objects that satisfy the funding model, including the extracted scores) are presented through the terminal interface.
As a further preferable embodiment of the above technical means, step S2 is specifically implemented as the following steps:
step S2.1: selecting K line data in a recent W period (W comprises previous continuous periods of a latest period and can be selected according to the requirements of a user) from a database, if the highest point is generated on the latest K line, selecting the stock into a stock library, and executing step S3;
step S2.2: if the peak does not occur in the latest period, the stock is not selected into the stock pool, and step 1 is performed (K-line data of the stock can be collected in real time until the peak occurs in the latest period).
As a further preferable embodiment of the above technical means, step S3 is specifically implemented as the following steps:
step S3.1: calculating the information of the stock through a first standard;
step S3.2: the information of the stock is calculated by the second standard.
As a further preferred embodiment of the above technical solution, step S3.1 is specifically implemented as the following steps:
step S3.1.1: respectively defining the lowest point price, the next highest point price, the next lowest point price and the highest point price of the stock as A, B, C and D in turn;
step S3.1.2: calculating price channels including slopes K and widths H for individual strands in the candidate pool (preferably, K ═ C-a)/AC (representing interval intervals, the same applies below), H ═ B- (C-a) × AB/AC-a, H% [ B- (C-a) × AB/AC-a ]/B);
step S3.1.3: calculating a lower orbit price A 'of the lowest point price A and the next highest point price B and a lower orbit price C' of the next lowest point price C and the highest point price D according to the slope K (preferably, A '═ AA' (C-A)/AC + A; C '═ AC' (C-A)/AC + A);
step S3.1.4: obtaining the highest point B 'between AB, and calculating the slope ((B-B')/B 'B) of B and B', if the slope of B and B 'is greater than the slope of C and the latest C, then B' is the latest B;
step S3.1.5: calculating a capital game point E corresponding to each K line after D corresponding to the slope and a main force cost price En corresponding to a later time period (after 10 points per day, D and E cannot be in the same K line, n is the time interval after E, preferably, the price E is BD interval (C price-A price)/AC interval + B price, and the price En is (BD interval + n) (C price-A price)/AC interval + B price);
step S3.1.6: and (3) calculating the selling point F of each period after breakthrough, and calculating the profitability after successful arrival (preferably, F ═ En price + H-X%. B price, X is an adjustable parameter, and the 15-minute period volume of transaction at E is limited to be recorded and is defined as L).
As a further preferable embodiment of the above technical solution, the step S3.1.3 is specifically implemented as the following steps:
step S3.1.3.1: if the price lower than C' is generated between CDs, the track is corrected, the lowest price between CDs is taken as the latest C, and the slope K is corrected;
step S3.1.3.2: if a price below A' occurs between AB, the orbit is modified, taking the lowest price between AB as the latest A and modifying the slope K.
As a further preferable embodiment of the above technical solution, the step S3.2 is implemented by further comprising the following steps in addition to the step S3.1:
step S3.2.1: all stock libraries after the fund game point E is generated are alternative libraries;
step S3.2.2: setting the first high point after the capital game point E as the price a (namely, the price a is considered to be effective if the two K lines after the price a do not exceed the price a, otherwise, the price a is invalid);
step S3.2.3: setting the second high point after the capital game point E as the price c (two K lines after the price c do not exceed the price c, the number of K lines between a and c is more than or equal to 2, and the price difference between ac (the price a can be lower than the price c) is less than (the price a-the price b) × X);
step S3.2.4: obtaining the lowest point between acs (representing interval, the same below) as the price b (the price difference between ab needs to be larger than X% of the price a);
step S3.2.5: starting tracking after the c price is generated, and if the d price point is close to the b price, making a prompt (namely the d price-b price is less than or equal to (c price-b price) × X);
step S3.2.6: if the point d appears at a preset time point (preferably two and a half afternoons), displaying the red taken position, and giving a blue risk prompt when the point b falls to the broken point;
step S3.2.7: and calculating the slope between the two prices ac, and acquiring the price En of the main force cost corresponding to each period after the price d.
As a more preferable mode of the above mode, the scoring system in step S4 sets a parameter weight according to the market environment.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the intelligent stock screening and evaluating method.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program that, when executed by a processor, performs the steps of the method for intelligent stock screening and evaluation.
Drawings
FIG. 1 is a trend chart of a first criterion of the intelligent stock screening and evaluation method of the invention.
Fig. 2 is a trend chart of a second standard of the intelligent stock screening and evaluating method of the invention.
Detailed Description
The following description is presented to disclose the invention so as to enable any person skilled in the art to practice the invention. The preferred embodiments in the following description are given by way of example only, and other obvious variations will occur to those skilled in the art. The basic principles of the invention, as defined in the following description, may be applied to other embodiments, variations, modifications, equivalents, and other technical solutions without departing from the spirit and scope of the invention.
Referring to fig. 1 of the drawings, fig. 1 is a trend chart of a first standard of the intelligent stock screening and evaluating method of the invention, and fig. 2 is a trend chart of a second standard of the intelligent stock screening and evaluating method of the invention.
In the preferred embodiment of the present invention, those skilled in the art should note that the K-line data, the highest price, the lowest price, etc. referred to in the present invention can be regarded as the prior art.
Preferred embodiments.
The invention discloses an intelligent stock screening and evaluating method, which is used for meeting information corresponding to stock tendency in a daily fluctuation state and comprises the following steps:
step S1: setting a fund model, downloading and collecting K-line data (including the highest price, the lowest price, the closing price, the volume of bargaining and the like of the stock in unit time) of the stock in real time and establishing a database;
step S2: selecting K-line data in a plurality of recent periods (including previous continuous periods of a latest period, which can be selected according to the requirements of a user) from a database, retrieving each data point (the data point comprises a highest point, a next place, a lowest point and the like) in the plurality of periods, and judging whether the highest point is generated in the latest period so as to judge whether to enter a stock library;
step S3: rejecting stock marks with unqualified investment style in a stock library according to the basic surface information to form a suitable alternative library (go to ST and go to market withdrawal);
step S4: a scoring system is set up by selecting each parameter (the parameters comprise 1. whether the parameter is in an alternative library, 2.A price, C price distance, 3.E time, 4. price in a tray, 5. price for opening a tray, 6. transaction amount, 7.a time, 8.C time, 9.d time, 10.E time, 11.B-C parameter, 12. not in a tray, 13. current stock price, 14.F time, 15.En price-current price, 16.H percent and the like)
Step S5: continuously screening real-time updated data in the database by the fund model according to a target screening mode meeting the asset targets, and extracting scores according to parameters (the scores can be continuously refreshed and changed along with the change of transaction time);
step S6: real-time reminders for individual stocks (pages of asset objects that satisfy the funding model, including the extracted scores) are presented through the terminal interface.
Specifically, step S2 is implemented as the following steps:
step S2.1: selecting K line data in a recent W period (W comprises previous continuous periods of a latest period and can be selected according to the requirements of a user) from a database, if the highest point is generated on the latest K line, selecting the stock into a stock library, and executing step S3;
step S2.2: if the peak does not occur in the latest period, the stock is not selected into the stock pool, and step 1 is performed (K-line data of the stock can be collected in real time until the peak occurs in the latest period).
More specifically, step S3 is specifically implemented as the following steps:
step S3.1: calculating the information of the stock through a first standard;
step S3.2: the information of the stock is calculated by the second standard.
Further, step S3.1 is embodied as the following steps:
step S3.1.1: respectively defining the lowest point price, the next highest point price, the next lowest point price and the highest point price of the stock as A, B, C and D in turn;
step S3.1.2: calculating price channels including slopes K and widths H for individual strands in the candidate pool (preferably, K ═ C-a)/AC (representing interval intervals, the same applies below), H ═ B- (C-a) × AB/AC-a, H% [ B- (C-a) × AB/AC-a ]/B);
step S3.1.3: calculating a lower orbit price A 'of the lowest point price A and the next highest point price B and a lower orbit price C' of the next lowest point price C and the highest point price D according to the slope K (preferably, A '═ AA' (C-A)/AC + A; C '═ AC' (C-A)/AC + A);
step S3.1.4: obtaining the highest point B 'between AB, and calculating the slope ((B-B')/B 'B) of B and B', if the slope of B and B 'is greater than the slope of C and the latest C, then B' is the latest B;
step S3.1.5: calculating a capital game point E corresponding to each K line after D corresponding to the slope and a main force cost price En corresponding to a later time period (after 10 points per day, D and E cannot be in the same K line, n is the time interval after E, preferably, the price E is BD interval (C price-A price)/AC interval + B price, and the price En is (BD interval + n) (C price-A price)/AC interval + B price);
step S3.1.6: and (3) calculating the selling point F of each period after breakthrough, and calculating the profitability after successful arrival (preferably, F ═ En price + H-X%. B price, X is an adjustable parameter, and the 15-minute period volume of transaction at E is limited to be recorded and is defined as L).
Further, step S3.1.3 is embodied as the following steps:
step S3.1.3.1: if the price lower than C' is generated between CDs, the track is corrected, the lowest price between CDs is taken as the latest C, and the slope K is corrected;
step S3.1.3.2: if a price below A' occurs between AB, the orbit is modified, taking the lowest price between AB as the latest A and modifying the slope K.
Preferably, step S3.2 is implemented to further include the following steps on the basis of step S3.1:
step S3.2.1: all stock libraries after the fund game point E is generated are alternative libraries;
step S3.2.2: setting the first high point after the capital game point E as the price a (namely, the price a is considered to be effective if the two K lines after the price a do not exceed the price a, otherwise, the price a is invalid);
step S3.2.3: setting the second high point after the capital game point E as the price c (two K lines after the price c do not exceed the price c, the number of K lines between a and c is more than or equal to 2, and the price difference between ac (the price a can be lower than the price c) is less than (the price a-the price b) × X);
step S3.2.4: obtaining the lowest point between acs (representing interval, the same below) as the price b (the price difference between ab needs to be larger than X% of the price a);
step S3.2.5: starting tracking after the c price is generated, and if the d price point is close to the b price, making a prompt (namely the d price-b price is less than or equal to (c price-b price) × X);
step S3.2.6: if the point d appears at a preset time point (preferably two and a half afternoons), displaying the red taken position, and giving a blue risk prompt when the point b falls to the broken point;
step S3.2.7: and calculating the slope between the two prices ac, and acquiring the price En of the main force cost corresponding to each period after the price d.
Preferably, the scoring system in step S4 further sets the parameter weight according to the market environment.
The invention also discloses an electronic device, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of the intelligent stock screening and evaluating method when executing the program.
Preferably, information (such as a stock code) of the required stock is input on a terminal page, namely, a score showing a score of the required stock, an update time, a time-sharing line, a day K line, a trend analysis and the like are displayed, a foreground evaluation of the required stock is provided for a user under the support of a big data algorithm, and a good use experience is provided for the user.
A non-transitory computer readable storage medium having stored thereon a computer program that, when executed by a processor, performs the steps of a method for intelligent stock screening and evaluation.
It should be noted that the technical features of the K-line data, the highest price, the lowest price, and the like related to the patent application of the present invention should be regarded as the prior art, and the specific structure, the operation principle, the control mode and the spatial arrangement mode of the technical features may be conventional in the art, and should not be regarded as the invention point of the patent application, and the patent application is not further specifically described in detail.
It will be apparent to those skilled in the art that modifications and equivalents may be made in the embodiments and/or portions thereof without departing from the spirit and scope of the present invention.
Claims (9)
1. An intelligent stock screening and evaluating method is used for meeting information corresponding to stock trends in a daily fluctuation state and is characterized by comprising the following steps of:
step S1: establishing a fund model, downloading and collecting K-line data of stocks in real time and establishing a database;
step S2: selecting K line data in a plurality of recent periods from a database, retrieving each data point in the plurality of periods and judging whether the highest point is generated in the latest period so as to judge whether to enter a stock library;
step S3: rejecting stock marks with unqualified investment style in the stock library according to the basic surface information to form a suitable alternative library;
step S4: a scoring system is established by selecting each parameter;
step S5: continuously screening the real-time updated data in the database by the fund model according to a target screening mode meeting the asset targets, and extracting scores according to the parameters;
step S6: and displaying the real-time reminding of each stock through a terminal interface.
2. The intelligent stock screening and evaluating method of claim 1, wherein the step S2 is implemented as the following steps:
step S2.1: selecting K line data in the recent W period from the database, if the highest point is generated in the latest K line, selecting the stock into the stock library, and executing step S3;
step S2.2: if the peak does not occur in the latest period, the stock is not selected in the stock pool and step 1 is performed.
3. The intelligent stock screening and evaluating method of claim 1, wherein the step S3 is implemented as the following steps:
step S3.1: calculating the information of the stock through a first standard;
step S3.2: the information of the stock is calculated by the second standard.
4. The intelligent stock screening and evaluating method of claim 3, wherein step S3.1 is implemented as the following steps:
step S3.1.1: respectively defining the lowest point price, the next highest point price, the next lowest point price and the highest point price of the stock as A, B, C and D in turn;
step S3.1.2: calculating a price channel comprising a slope K and a width H of each stock in the alternative library;
step S3.1.3: calculating a lower orbit price A 'of the lowest point price A and the next highest point price B and a lower orbit price C' of the next lowest point price C and the highest point price D according to the slope K;
step S3.1.4: obtaining the highest point B 'between AB, and calculating the slope ((B-B')/B 'B) of B and B', if the slope of B and B 'is greater than the slope of C and the latest C, then B' is the latest B;
step S3.1.5: solving a fund game point E corresponding to each K line after D corresponding to the slope and a main force cost price En price corresponding to a later time period;
step S3.1.6: and (4) solving the selling point F in each period after breakthrough, and calculating the profitability after successful arrival.
5. The intelligent stock screening and evaluating method of claim 4, wherein the step S3.1.3 is implemented as the following steps:
step S3.1.3.1: if the price lower than C' is generated between CDs, the track is corrected, the lowest price between CDs is taken as the latest C, and the slope K is corrected;
step S3.1.3.2: if a price below A' occurs between AB, the orbit is modified, taking the lowest price between AB as the latest A and modifying the slope K.
6. The intelligent stock screening and evaluating method of claim 5, wherein step S3.2 is implemented by further comprising the following steps based on step S3.1:
step S3.2.1: all stock libraries after the fund game point E is generated are alternative libraries;
step S3.2.2: setting the first high point behind the fund game point E as a price;
step S3.2.3: setting the price c as the second high point after the capital game point E;
step S3.2.4: obtaining the lowest point between ac and setting the lowest point as the price b;
step S3.2.5: tracking is started after the price c is generated, and if the price d is close to the price b, a prompt is given;
step S3.2.6: if the point d appears at a preset time point, displaying the red taken position, and performing blue risk prompt when the point b is broken;
step S3.2.7: and calculating the slope between the two prices ac, and acquiring the price En of the main force cost corresponding to each period after the price d.
7. The method as claimed in claim 1, wherein the scoring system in step S4 further sets the parameter weight according to market environment.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for intelligent stock screening and evaluation according to any one of claims 1 to 7 when executing the program.
9. A non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps of a method for intelligent screening and evaluation of stocks according to any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113034278A (en) * | 2021-03-10 | 2021-06-25 | 深圳前海嘉可能信息科技有限公司 | Stock software-based 3-buying alarm method |
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| CN113034278A (en) * | 2021-03-10 | 2021-06-25 | 深圳前海嘉可能信息科技有限公司 | Stock software-based 3-buying alarm method |
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