Security transaction intelligent analysis and decision support system and method

Abstract

The invention specifically relates to a security transaction intelligent analysis and decision support system and method. The method comprises the following steps: data integration; transaction behavior analysis: analyzing the transaction information data of the user to obtain a transaction evaluation value; evaluating the market environment; evaluating the risk adaptation degree; and decision support. According to the method, user transaction behavior data, market environment characteristics and psychological stress indexes are integrated, and a multi-dimensional risk assessment model is constructed; the position dispersion degree is quantified, and three-dimensional evaluation of the risk bearing capacity of the user is realized in combination with geometric models of stop loss operation values and risk lever values; psychological factors such as decision hesitation time consumption and order modification frequency are brought into risk calculation, and the comprehensiveness and accuracy of risk assessment are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of securities trading, and in particular to a securities trading intelligent analysis and decision support system and method. Background Art

[0002] Securities trading analysis and decision support systems are gradually evolving from traditional manual experience judgment to data-driven intelligence. However, existing technologies still have significant shortcomings in user behavior analysis, market environment assessment, and personalized strategy generation.

[0003] Traditional methods mostly rely on static risk questionnaires or single trading indicators (such as turnover rate, profit and loss ratio), ignoring the dynamic characteristics of user trading behavior;

[0004] Current market analysis mainly relies on single-dimensional indicators such as historical volatility and trading volume, which are difficult to dynamically reflect changes in market risks;

[0005] Existing decision support systems are mostly based on fixed rules (such as "low PE buy") or general models (such as mean-variance optimization) and lack dynamic adaptation capabilities;

[0006] Therefore, a securities trading intelligent analysis and decision support system and method are needed to address the above-mentioned problems. Summary of the invention

[0007] The purpose of the present invention is to propose a securities trading intelligent analysis and decision support system and method in order to solve the above problems.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] A securities trading intelligent analysis and decision support method, comprising the following parts:

[0010] Data integration: Obtain user transaction information data and market data, and pre-process the acquired data;

[0011] Transaction behavior analysis: Analyze the user's transaction information data to obtain the transaction evaluation value;

[0012] Market environment assessment: Analyze market data to obtain market assessment value;

[0013] Risk suitability assessment: The transaction evaluation value, market evaluation value and preset pressure coefficient are combined for comprehensive analysis to obtain the user's risk suitability index;

[0014] Decision support: Determine investment decision recommendations for users based on their risk suitability index.

[0015] Preferably, the transaction evaluation value obtained after analyzing the transaction information data of the user specifically includes the following parts:

[0016] After analyzing each of the user's securities, the position dispersion, stop loss operation value and risk leverage value are obtained respectively, and the position dispersion, stop loss operation value and risk leverage value are processed comprehensively to obtain the transaction evaluation value;

[0017] After normalizing the position dispersion, stop-loss operation value and risk leverage value, use the position dispersion and stop-loss operation value as the two right-angled sides of a right triangle respectively. Connect the remaining side to form a complete right triangle. Use the risk leverage value as the height of the right triangle to construct a triangular pyramid model. Calculate the volume of the triangular pyramid model and use the volume of the triangular pyramid model as the transaction evaluation value.

[0018] Preferably, the position dispersion is obtained after analyzing each of the user's securities, which specifically includes the following parts:

[0019] Obtain the number of securities held by the user, determine the market value of each security held, and accumulate the market value of each security held to obtain the total holding market value; divide the market value of each security held by the total holding market value in turn to obtain the proportion of the market value of each security held to the total holding market value, and obtain the holding dispersion through calculation.

[0020] Preferably, the process of obtaining the stop loss operation value is as follows:

[0021] Obtain the preset stop loss price of each security within the preset time period, and the number of operations of selling the security when the price of each security reaches the stop loss price, divide the number of operations of selling each security by the total number of transactions of each security, and obtain the stop loss frequency of each security; calculate the average of the stop loss frequencies of each security and obtain the average of the stop loss frequencies;

[0022] Extract the selling volume corresponding to each selling operation of the securities and the corresponding holding volume before the selling operation; divide the selling volume corresponding to each selling operation by the corresponding holding volume before the selling operation to obtain the selling ratio, and record the largest selling ratio as the maximum selling ratio;

[0023] Obtain the maximum selling ratio of each security in turn, extract the maximum selling ratio from them, and record it as the extreme selling ratio;

[0024] Preset the weight factors of the average stop loss frequency and the extreme selling ratio, multiply the average stop loss frequency and the extreme selling ratio by their corresponding weight factors, and then sum them up to get the stop loss operation value.

[0025] Preferably, the process of obtaining the risk leverage value is as follows:

[0026] Obtain the user's own funds and financing funds, accumulate the own funds and financing funds to get the total funds, and use the total funds for securities trading; divide the total funds by the own funds to get the leverage ratio;

[0027] Obtain the distribution of the types and sectors of securities held by the user within the preset time period, as well as the holding amount of securities of each type and sector; divide the holding amount of securities of each type and sector by the total funds to obtain the personal amount proportion of securities of each type and sector;

[0028] Select a preset number of investors to assign risk scores to the various types and sectors of securities held by the user, with scores ranging from 0 to 10, with the scores being proportional to the risk;

[0029] Multiply the user's personal amount ratio of each type and sector of securities by the corresponding risk score, then sum them up, and divide the sum by the total number of securities held by the user to get the risk rate;

[0030] After normalizing the leverage ratio and risk rate, use the leverage ratio as one right-angled side of the right triangle, use the risk rate as the other right-angled side of the right triangle, and connect the remaining side lengths to obtain a complete right triangle; calculate the area of ​​the right triangle and use the area as the risk leverage value.

[0031] Preferably, the market evaluation value obtained after analyzing the market data specifically includes the following parts:

[0032] The annualized volatility of each security is obtained by calculating the yield sequence of each security price and the mean of the yield and then calculating the standard deviation; the maximum annualized volatility is extracted from each annualized volatility and recorded as the maximum volatility;

[0033] Obtain the trading volume and circulating share capital of each security in a preset time period, divide the circulating share capital by the trading volume to obtain the retention rate of each security; calculate the average of the retention rates of each security to obtain the average retention rate;

[0034] Obtain the bid and ask prices of each security in the market, extract the highest bid and the lowest ask prices, record the difference between the highest bid and the lowest ask prices of each security as the bid-ask spread, and extract the maximum bid-ask spread;

[0035] The market valuation of each security is obtained by comprehensively processing the maximum volatility, the average retained value, and the maximum bid-ask spread.

[0036] Preferably, the process of obtaining the pressure coefficient is as follows:

[0037] Obtaining the user's operation data during the securities trading process, including the time interval from clicking the order button to confirming the order submission in each order placement operation of the user during the securities trading process, which is recorded as the operation time;

[0038] Obtain the time interval between two consecutive securities transactions of the user, preset a transaction interval time threshold, and accumulate the transaction time intervals greater than the transaction interval time threshold to obtain the number of hesitation times;

[0039] Obtain the number of times the user has modified the submitted order within a preset time period, extract the transaction amount corresponding to each modification, preset a transaction amount threshold, compare the transaction amount corresponding to each modification with the transaction amount threshold, record the transaction amount greater than the transaction amount threshold as the pressure amount, and accumulate all the pressure amounts to obtain the total pressure amount;

[0040] The pressure coefficient is obtained by comprehensively processing the operation time, hesitation times and total pressure.

[0041] Preferably, the risk adaptation index of the user is obtained by comprehensively analyzing the transaction evaluation value, the market evaluation value and the preset pressure coefficient, which specifically includes the following parts:

[0042] The weight factors of the preset transaction evaluation value, market evaluation value and pressure coefficient are respectively multiplied by the transaction evaluation value, market evaluation value and pressure coefficient and their corresponding weight factors and then summed up to obtain the risk adaptation index.

[0043] Preferably, determining the user's investment decision suggestion based on the user's risk suitability index specifically includes:

[0044] Three groups of threshold value ranges are preset, each of which corresponds to a strategy state. The risk adaptation index is matched with the three groups of preset threshold value ranges to obtain the strategy state corresponding to the risk adaptation index, where the strategy state includes defense strategy, balance strategy, and aggressive strategy;

[0045] Make corresponding strategy support recommendations based on the strategy status corresponding to the risk adaptation index;

[0046] Defensive strategies: increase the proportion of fixed-income assets, allocate cash or money market funds at a preset ratio, reduce investment in equity assets, strictly control positions, set strict stop-loss and take-profit points, and reduce trading frequency;

[0047] Balance strategy: Balance the allocation of various assets, diversify investments, reasonably control positions, flexibly adjust stop-loss and take-profit points, and rebalance assets in a timely manner;

[0048] Aggressive strategy: Increase the proportion of equity assets: participate in high-risk investment products, reduce the proportion of fixed-income assets and cash, increase position levels, dynamically adjust the investment portfolio, and flexibly use stop-loss and take-profit strategies.

[0049] A securities trading intelligent analysis and decision support system, including the following parts:

[0050] Data collection and processing module: obtains user transaction information data and market data, and pre-processes the acquired data;

[0051] Data analysis module: Analyzes the user's transaction information data to obtain the transaction evaluation value;

[0052] Market environment analysis module: Analyze market data to obtain market evaluation value;

[0053] Risk assessment module: The transaction assessment value, market assessment value and preset pressure coefficient are combined for comprehensive analysis to obtain the user's risk adaptation index;

[0054] Decision support module: Determine the user's investment decision recommendations based on the user's risk suitability index.

[0055] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0056] 1. The present invention constructs a multi-dimensional risk assessment model by integrating user transaction behavior data, market environment characteristics and psychological stress indicators; quantifies the position dispersion, combines the geometric model of stop loss operation value and risk leverage value, and realizes a three-dimensional assessment of the user's risk tolerance; incorporates psychological factors such as decision-making hesitation time and order modification frequency into risk calculation, which significantly improves the comprehensiveness and accuracy of risk assessment.

[0057] 2. The present invention matches defense, balance or aggressive strategies in real time according to the user's risk tolerance and market environment, and differentiates the asset ratio and operation rules. When the market volatility exceeds the threshold, the stop loss point is automatically tightened and the equity position is reduced. If the user's stress coefficient increases, even if the risk adaptation index is in the aggressive range, it is still recommended to reduce the use of leverage. This mechanism breaks through the limitations of traditional fixed strategies, and through real-time data-driven strategy adjustments, it effectively balances returns and risks, thereby improving the intelligence level of investment decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0059] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0060] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete, and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0061] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless explicitly defined as such herein.

[0062] See also Figure 1 As shown, the present invention provides a technical solution:

[0063] A securities trading intelligent analysis and decision support method, comprising the following parts:

[0064] Data integration: Obtain user transaction information data and market data, and pre-process the acquired data;

[0065] Obtain the user's transaction details through the brokerage trading software;

[0066] The user's transaction information data includes: the time of each transaction, the type of securities traded, the direction of buying and selling, the transaction quantity and the transaction price;

[0067] Obtain market data by accessing financial data platforms such as Wind and Bloomberg;

[0068] Market data includes: historical price trends, trading volumes, technical indicator data of different periods (such as moving averages, relative strength index, etc.) of each security; as well as collection of macroeconomic data, such as gross domestic product (GDP) growth rate, inflation rate, interest rate, exchange rate, etc.;

[0069] After cleaning the data, store it in the database;

[0070] Transaction behavior analysis: Analyze the user's transaction information data to obtain the transaction evaluation value;

[0071] After analyzing the user's transaction information data, the transaction evaluation value is obtained, which specifically includes the following parts:

[0072] After analyzing each of the user's securities, the position dispersion, stop loss operation value and risk leverage value are obtained respectively, and the position dispersion, stop loss operation value and risk leverage value are processed comprehensively to obtain the transaction evaluation value;

[0073] After normalizing the position dispersion, stop-loss operation value and risk leverage value, the position dispersion and stop-loss operation value are used as the two right-angled sides of a right triangle respectively. The remaining side is connected to form a complete right triangle. The risk leverage value is used as the height of the right triangle to construct a triangular pyramid model, calculate the volume of the triangular pyramid model, and use the volume of the triangular pyramid model as the transaction evaluation value;

[0074] After analyzing each of the user's securities, the position dispersion is obtained, which includes the following parts:

[0075] Obtain the number of securities held by the user, determine the market value of each security held, and accumulate the market value of each security held to obtain the total holding market value; divide the market value of each security held by the total holding market value in turn to obtain the proportion of the market value of each security held to the total holding market value, and obtain the holding dispersion through calculation;

[0076] Use the Herfindahl-Hirschman Index to measure the dispersion of holdings: ;

[0077] Where i is the number of securities held, ;

[0078] It is the ratio of the market value of various securities held to the total market value of holdings;

[0079] The value of HHI ranges from 0 to 1;

[0080] If HHI is close to 0, it means that the holdings are very dispersed, the user has evenly distributed funds to a variety of securities, and the impact of a single security on the portfolio is small, and the risk is relatively low; for example, when a user holds a variety of stocks from different industries and types, and the holding ratio of each stock is small, the HHI value will be very low;

[0081] If the HHI is close to 1, it means that the holdings are highly concentrated. The user may have concentrated most of the funds on a few securities, and the single security risk faced by the investment portfolio is relatively large. For example, if the user concentrates most of the funds on a hot stock, then the HHI value will be high.

[0082] The process of obtaining the stop loss operation value is as follows:

[0083] Obtain the preset stop loss price of each security within the preset time period, and the number of operations of selling the security when the price of each security reaches the stop loss price, divide the number of operations of selling each security by the total number of transactions of each security, and obtain the stop loss frequency of each security; calculate the average of the stop loss frequencies of each security and obtain the average of the stop loss frequencies;

[0084] Extract the selling volume corresponding to each selling operation of the securities and the corresponding holding volume before the selling operation; divide the selling volume corresponding to each selling operation by the corresponding holding volume before the selling operation to obtain the selling ratio, and record the largest selling ratio as the maximum selling ratio;

[0085] Obtain the maximum selling ratio of each security in turn, extract the maximum selling ratio from them, and record it as the extreme selling ratio;

[0086] Preset the weight factors of the stop loss frequency mean and the selling ratio extreme value, multiply the stop loss frequency mean and the selling ratio extreme value by their corresponding weight factors, and then sum them up to get the stop loss operation value;

[0087] The process of obtaining the risk leverage value is as follows:

[0088] Obtain the user's own funds and financing funds, accumulate the own funds and financing funds to get the total funds, and use the total funds for securities trading; divide the total funds by the own funds to get the leverage ratio;

[0089] Obtain the distribution of the types and sectors of securities held by the user within the preset time period, as well as the holding amount of securities of each type and sector; divide the holding amount of securities of each type and sector by the total funds to obtain the personal amount proportion of securities of each type and sector;

[0090] Select a preset number of investors to assign risk scores to the various types and sectors of securities held by the user, with scores ranging from 0 to 10, with the scores being proportional to the risk;

[0091] Multiply the user's personal amount ratio of each type and sector of securities by the corresponding risk score, then sum them up, and divide the sum by the total number of securities held by the user to get the risk rate;

[0092] After normalizing the leverage ratio and risk rate, use the leverage ratio as one right-angled side of the right triangle, use the risk rate as the other right-angled side of the right triangle, and connect the remaining sides to get a complete right triangle; calculate the area of ​​the right triangle and use the area as the risk leverage value;

[0093] Market environment assessment: Analyze market data to obtain market assessment value;

[0094] After analyzing the market data, the market valuation is obtained, which includes the following parts:

[0095] The annualized volatility of each security is obtained by calculating the yield sequence of each security price and the mean of the yield and then calculating the standard deviation; the maximum annualized volatility is extracted from each annualized volatility and recorded as the maximum volatility;

[0096] It includes the following parts: Preset is the price of the security at time t, then the rate of return at time t is: ; After calculating the mean of the yield, we get , the standard deviation is calculated as: , where n is the sample size of the yield data; the larger the standard deviation, the more volatile the security price fluctuations;

[0097] Annualization is performed on the basis of standard deviation to facilitate comparison of different investment periods; assuming is the sample standard deviation, T is the number of trading days in a year. Usually, the stock market is calculated as 252 trading days a year, and the futures market may be different. The annualized volatility is ;

[0098] Obtain the trading volume and circulating share capital of each security in a preset time period, divide the circulating share capital by the trading volume to obtain the retention rate of each security; calculate the average of the retention rates of each security to obtain the average retention rate;

[0099] Obtain the bid and ask prices of each security in the market, extract the highest bid and the lowest ask prices, record the difference between the highest bid and the lowest ask prices of each security as the bid-ask spread, and extract the maximum bid-ask spread;

[0100] The market valuation of the security is obtained by comprehensively processing the maximum volatility, the average value of the retained amount, and the maximum bid-ask spread;

[0101] Preset the weight factors of maximum volatility, average retained value, and maximum bid-ask spread, and multiply the maximum volatility, average retained value, and maximum bid-ask spread with their corresponding weight factors and then sum them to obtain the market valuation of the security;

[0102] Risk suitability assessment: The transaction evaluation value, market evaluation value and preset pressure coefficient are combined for comprehensive analysis to obtain the user's risk suitability index;

[0103] The process of obtaining the pressure coefficient is as follows:

[0104] Obtaining the user's operation data during the securities trading process, including the time interval from clicking the order button to confirming the order submission in each order placement operation of the user during the securities trading process, which is recorded as the operation time;

[0105] Obtain the time interval between two consecutive securities transactions of the user, preset a transaction interval time threshold, and accumulate the transaction time intervals greater than the transaction interval time threshold to obtain the number of hesitation times;

[0106] Obtain the number of times the user has modified the submitted order within a preset time period, extract the transaction amount corresponding to each modification, preset a transaction amount threshold, compare the transaction amount corresponding to each modification with the transaction amount threshold, record the transaction amount greater than the transaction amount threshold as the pressure amount, and accumulate all the pressure amounts to obtain the total pressure amount;

[0107] The pressure coefficient is obtained by comprehensively processing the operation time, the number of hesitations, and the total pressure.

[0108] Preset the weight factors of operation time, hesitation times, and total pressure, respectively multiply the operation time, hesitation times, and total pressure with their corresponding weight factors and then sum them to obtain the pressure coefficient;

[0109] The user's risk adaptation index is obtained by comprehensively analyzing the transaction evaluation value, market evaluation value and the preset pressure coefficient, which specifically includes the following parts:

[0110] Preset the weight factors of the transaction evaluation value, market evaluation value and pressure coefficient, respectively multiply the transaction evaluation value, market evaluation value and pressure coefficient with their corresponding weight factors and then sum them up to obtain the risk adaptation index;

[0111] Decision support: Determine investment decision recommendations for users based on their risk suitability index;

[0112] Determine the user's investment decision suggestions based on the user's risk suitability index, including:

[0113] Three groups of threshold value ranges are preset, each of which corresponds to a strategy state. The risk adaptation index is matched with the three groups of preset threshold value ranges to obtain the strategy state corresponding to the risk adaptation index, where the strategy state includes defense strategy, balance strategy, and aggressive strategy;

[0114] Make corresponding strategy support recommendations based on the strategy status corresponding to the risk adaptation index;

[0115] Defense strategy: When the risk adaptation index is within the threshold value range corresponding to the defense strategy, it indicates that the user's risk tolerance is low and the market environment may have greater uncertainty or risk. At this time, a conservative and prudent investment strategy should be adopted to ensure the security and stability of assets;

[0116] Increase the proportion of fixed-income assets: allocate a larger proportion of funds to fixed-income products such as government bonds and high-credit-rating corporate bonds; allocate cash or money market funds at a preset ratio: maintain a certain proportion of cash or invest in money market funds to ensure the liquidity of assets; money market funds have the characteristics of high liquidity and low risk, and can be used as reserve funds to deal with emergencies or seize investment opportunities; it is recommended to allocate 10% to 20% of assets to cash or money market funds; reduce investment in equity assets: significantly reduce the investment proportion of equity assets such as stocks and stock funds, and control it within 10% to 30% of assets;

[0117] Strictly control positions: avoid overinvestment and maintain a low position level; it is generally recommended to control the overall position at 30% to 50% to reduce the impact of market fluctuations on assets; set strict stop loss and stop profit points: when making any investment, clear stop loss and stop profit points must be set in advance; the setting of stop loss points should be reasonably determined based on the volatility of assets and personal risk tolerance, and can generally be set at around 5% to 10% of the investment cost; the stop profit point can be flexibly adjusted according to market conditions and investment goals, for example, when the investment income reaches 10% to 20%, you can consider stopping profit;

[0118] Reduce trading frequency: Avoid frequent trading to reduce transaction costs and risks brought by market fluctuations; in unstable markets, frequent buying and selling may increase the probability of investment errors;

[0119] Balanced strategy: When the risk adaptation index is within the threshold value range corresponding to the balanced strategy, it indicates that the user has a certain risk tolerance and the market environment is relatively stable, but there is still a certain degree of uncertainty. At this time, an investment strategy that balances risks and returns should be adopted, and asset appreciation should be moderately pursued on the premise of ensuring asset safety.

[0120] Balanced allocation of various assets: Allocate funds relatively evenly among fixed-income assets, equity assets, and cash or money market funds;

[0121] For example, 40% to 60% of assets can be allocated to fixed-income assets, 30% to 50% to equity assets, and 10% to 20% to cash or money market funds;

[0122] Diversification: Diversify investments across asset classes to reduce the risk of a single asset or industry;

[0123] For example, in equity assets, you can invest in stocks or funds of different industries and sizes; in fixed-income assets, you can invest in bonds of different maturities and credit ratings;

[0124] Reasonable control of positions: The overall position can be maintained at around 50% to 70%, and can be adjusted flexibly according to market conditions; when the market shows a clear upward or downward trend, the position can be appropriately increased or decreased;

[0125] Flexible adjustment of stop loss and take profit points: according to the performance of assets and market conditions, stop loss and take profit points can be adjusted in a timely manner; when the market is rising, the take profit point can be appropriately raised to obtain more profits; when the market is falling, the stop loss point can be adjusted in time to control losses;

[0126] Rebalance assets in a timely manner: Evaluate and adjust the investment portfolio regularly to restore the asset allocation ratio to the target level; for example, when the increase in equity assets is large, causing their proportion in the investment portfolio to exceed the target ratio, some equity assets can be sold and fixed-income assets can be purchased to maintain a balanced asset allocation;

[0127] Aggressive strategy: When the risk adaptation index is within the threshold value range corresponding to the aggressive strategy, it indicates that the user has a high risk tolerance, the market environment is relatively optimistic, and there are more investment opportunities; at this time, an aggressive investment strategy should be adopted to pursue higher investment returns;

[0128] Increase the proportion of equity assets: Allocate a larger proportion of funds to equity assets such as stocks and stock funds, which can reach 60% to 80% or even higher of assets; equity assets have greater appreciation potential when the market rises, but they are also accompanied by higher risks;

[0129] Participation in high-risk investment products: You can consider participating in some high-risk, high-return investment products, such as futures, options and other derivatives markets, but you should pay attention to controlling the investment ratio, generally not exceeding 10% to 20% of assets; these investment products have a high leverage effect, which can greatly magnify returns when the market is favorable, but may also lead to huge losses;

[0130] Reduce the proportion of fixed-income assets and cash: Keep the investment proportion of fixed-income assets and cash or money market funds at a low level, about 10% to 30% and 5% to 10% respectively;

[0131] Improve the position level: The overall position can be maintained at 70% - 90% or even higher, making full use of the opportunity of market rise to gain profits; but pay attention to changes in market risks and adjust the position in time;

[0132] Dynamically adjust investment portfolio: Pay close attention to market dynamics and industry trends and adjust investment portfolio in a timely manner;

[0133] For example, when an industry is found to have great development potential, investment in stocks or funds related to the industry can be increased; when adverse changes occur in the market, high-risk assets can be promptly reduced;

[0134] Flexible use of stop-loss and take-profit strategies: While pursuing high returns, we must also pay attention to risk control; set reasonable stop-loss and take-profit points, and flexibly adjust them according to market conditions;

[0135] For example, in the early stage of market rise, the stop loss point can be appropriately relaxed to avoid selling too early and missing the rising opportunity; when the market is close to the top, the take profit point can be tightened in time to lock in the profit;

[0136] A securities trading intelligent analysis and decision support system, including the following parts:

[0137] Data collection and processing module: obtains user transaction information data and market data, and pre-processes the acquired data;

[0138] Data analysis module: Analyzes the user's transaction information data to obtain the transaction evaluation value;

[0139] Market environment analysis module: Analyze market data to obtain market evaluation value;

[0140] Risk assessment module: The transaction assessment value, market assessment value and preset pressure coefficient are combined for comprehensive analysis to obtain the user's risk adaptation index;

[0141] Decision support module: Determine the user's investment decision recommendations based on the user's risk suitability index.

[0142] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factor and specific coefficient value in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0143] The above description of the embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A securities trading intelligent analysis and decision support method, characterized in that: Includes the following parts: Data integration: Obtain user transaction information data and market data, and pre-process the acquired data; Transaction behavior analysis: Analyze the user's transaction information data to obtain the transaction evaluation value; Market environment assessment: Analyze market data to obtain market assessment value; Risk suitability assessment: The transaction evaluation value, market evaluation value and preset pressure coefficient are combined for comprehensive analysis to obtain the user's risk suitability index; Decision support: Determine investment decision recommendations for users based on their risk suitability index.

2. A securities trading intelligent analysis and decision support method according to claim 1, characterized in that: The transaction evaluation value obtained by analyzing the transaction information data of the user specifically includes the following parts: After analyzing each of the user's securities, the position dispersion, stop loss operation value and risk leverage value are obtained respectively, and the position dispersion, stop loss operation value and risk leverage value are processed comprehensively to obtain the transaction evaluation value; After normalizing the position dispersion, stop-loss operation value and risk leverage value, use the position dispersion and stop-loss operation value as the two right-angled sides of a right triangle respectively. Connect the remaining side to form a complete right triangle. Use the risk leverage value as the height of the right triangle to construct a triangular pyramid model. Calculate the volume of the triangular pyramid model and use the volume of the triangular pyramid model as the transaction evaluation value.

3. A securities trading intelligent analysis and decision support method according to claim 2, characterized in that: After analyzing each of the user's securities, the position dispersion is obtained, which specifically includes the following parts: Obtain the number of securities held by the user, determine the market value of each security held, and accumulate the market value of each security held to obtain the total holding market value; divide the market value of each security held by the total holding market value in turn to obtain the proportion of the market value of each security held to the total holding market value, and obtain the holding dispersion through calculation.

4. A securities trading intelligent analysis and decision support method according to claim 2, characterized in that: The process of obtaining the stop loss operation value is as follows: Obtain the preset stop loss price of each security within the preset time period, and the number of operations of selling the security when the price of each security reaches the stop loss price, divide the number of operations of selling each security by the total number of transactions of each security, and obtain the stop loss frequency of each security; calculate the average of the stop loss frequencies of each security and obtain the average of the stop loss frequencies; Extract the selling volume corresponding to each selling operation of the securities and the corresponding holding volume before the selling operation; divide the selling volume corresponding to each selling operation by the corresponding holding volume before the selling operation to obtain the selling ratio, and record the largest selling ratio as the maximum selling ratio; Obtain the maximum selling ratio of each security in turn, extract the maximum selling ratio from them, and record it as the extreme selling ratio; Preset the weight factors of the average stop loss frequency and the extreme selling ratio, multiply the average stop loss frequency and the extreme selling ratio by their corresponding weight factors, and then sum them up to get the stop loss operation value.

5. A securities trading intelligent analysis and decision support method according to claim 2, characterized in that: The process of obtaining the risk leverage value is as follows: Obtain the user's own funds and financing funds, accumulate the own funds and financing funds to get the total funds, and use the total funds for securities trading; divide the total funds by the own funds to get the leverage ratio; Obtain the distribution of the types and sectors of securities held by the user within the preset time period, as well as the holding amount of securities of each type and sector; divide the holding amount of securities of each type and sector by the total funds to obtain the personal amount proportion of securities of each type and sector; Select a preset number of investors to assign risk scores to the various types and sectors of securities held by the user, with scores ranging from 0 to 10, with the scores being proportional to the risk; Multiply the user's personal amount ratio of each type and sector of securities by the corresponding risk score, then sum them up, and divide the sum by the total number of securities held by the user to get the risk rate; After normalizing the leverage ratio and risk rate, use the leverage ratio as one right-angled side of the right triangle, use the risk rate as the other right-angled side of the right triangle, and connect the remaining side lengths to obtain a complete right triangle; calculate the area of ​​the right triangle and use the area as the risk leverage value.

6. A securities trading intelligent analysis and decision support method according to claim 1, characterized in that: The market evaluation value obtained by analyzing the market data specifically includes the following parts: The annualized volatility of each security is obtained by calculating the yield sequence of each security price and the mean of the yield and then calculating the standard deviation; the maximum annualized volatility is extracted from each annualized volatility and recorded as the maximum volatility; Obtain the trading volume and circulating share capital of each security in a preset time period, divide the circulating share capital by the trading volume to obtain the retention rate of each security; calculate the average of the retention rates of each security to obtain the average retention rate; Obtain the bid and ask prices of each security in the market, extract the highest bid and the lowest ask prices, record the difference between the highest bid and the lowest ask prices of each security as the bid-ask spread, and extract the maximum bid-ask spread; The market valuation of each security is obtained by comprehensively processing the maximum volatility, the average retained value, and the maximum bid-ask spread.

7. A securities trading intelligent analysis and decision support method according to claim 1, characterized in that: The process of obtaining the pressure coefficient is as follows: Obtaining the user's operation data during the securities trading process, including the time interval from clicking the order button to confirming the order submission in each order placement operation of the user during the securities trading process, which is recorded as the operation time; Obtain the time interval between two consecutive securities transactions of the user, preset a transaction interval time threshold, and accumulate the transaction time intervals greater than the transaction interval time threshold to obtain the number of hesitation times; Obtain the number of times the user has modified the submitted order within a preset time period, extract the transaction amount corresponding to each modification, preset a transaction amount threshold, compare the transaction amount corresponding to each modification with the transaction amount threshold, record the transaction amount greater than the transaction amount threshold as the pressure amount, and accumulate all the pressure amounts to obtain the total pressure amount; The pressure coefficient is obtained by comprehensively processing the operation time, hesitation times and total pressure.

8. A securities trading intelligent analysis and decision support method according to claim 7, characterized in that: The risk adaptation index of the user is obtained by comprehensively analyzing the transaction evaluation value, the market evaluation value and the preset pressure coefficient, which specifically includes the following parts: The weight factors of the preset transaction evaluation value, market evaluation value and pressure coefficient are respectively multiplied by the transaction evaluation value, market evaluation value and pressure coefficient and their corresponding weight factors and then summed up to obtain the risk adaptation index.

9. A securities trading intelligent analysis and decision support method according to claim 8, characterized in that: The determining of the user's investment decision suggestion based on the user's risk suitability index specifically includes: Three groups of threshold value ranges are preset, each of which corresponds to a strategy state. The risk adaptation index is matched with the three groups of preset threshold value ranges to obtain the strategy state corresponding to the risk adaptation index, where the strategy state includes defense strategy, balance strategy, and aggressive strategy; Make corresponding strategy support recommendations based on the strategy status corresponding to the risk adaptation index; Defensive strategies: increase the proportion of fixed-income assets, allocate cash or money market funds at a preset ratio, and reduce investment in equity assets; strictly control positions, set strict stop-loss and take-profit points, and reduce trading frequency; Balance strategy: Balance the allocation of various assets, diversify investments, reasonably control positions, flexibly adjust stop-loss and take-profit points, and rebalance assets in a timely manner; Aggressive strategy: Increase the proportion of equity assets: participate in high-risk investment products, reduce the proportion of fixed-income assets and cash; as well as increase position levels, dynamically adjust investment portfolios, and flexibly use stop-loss and take-profit strategies.

10. A securities trading intelligent analysis and decision support system, using a securities trading intelligent analysis and decision support method according to any one of claims 1 to 9, characterized in that: Includes the following parts: Data collection and processing module: obtains user transaction information data and market data, and pre-processes the acquired data; Data analysis module: Analyzes the user's transaction information data to obtain the transaction evaluation value; Market environment analysis module: Analyze market data to obtain market evaluation value; Risk assessment module: The transaction assessment value, market assessment value and preset pressure coefficient are combined for comprehensive analysis to obtain the user's risk adaptation index; Decision support module: Determine the user's investment decision recommendations based on the user's risk suitability index.

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