CN116385176A - Transaction data monitoring system and method for investment transaction system - Google Patents
Transaction data monitoring system and method for investment transaction system Download PDFInfo
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Abstract
The invention discloses a transaction data monitoring system and method of an investment transaction system, which relate to the technical field of investment transaction data monitoring and comprise a data acquisition module, a comprehensive analysis module and a judgment module; the data acquisition module acquires the investment transaction historical data and the investment transaction risk data and transmits the investment transaction historical data and the investment transaction risk data to the comprehensive analysis module. The invention generates the risk index by collecting the historical data of the investment transaction and the risk data of the investment transaction, monitors multiple items of transaction data simultaneously by the generated risk index, realizes more accurate monitoring of the risk of the investment transaction, and timely prompts the investment transaction person when the high risk condition occurs in the investment transaction, thereby being convenient for the investment transaction person to timely find the investment risk problem, timely carrying out strategy adjustment on the investment risk and being convenient for efficiently managing the investment transaction risk.
Description
Technical Field
The invention relates to the technical field of investment transaction data monitoring, in particular to a transaction data monitoring system and method of an investment transaction system.
Background
Investment transactions refer to the act of buying and selling financial assets to increase capital or obtain revenue. Investment trading typically involves buying and selling financial assets, such as stocks, bonds, futures, options, foreign exchange, etc., intended to make use of market price fluctuations, price differences, and risk arbitrage opportunities to earn money.
An investment trading system refers to computer software or platform for conducting financial market exchanges. These systems provide various functions including market data analysis, transaction execution, order management, risk management, and reporting, among others. Investment trading systems are typically developed by professional financial and technological companies or securities companies in order to provide a quick, reliable and secure trading environment. Investment traders can trade, monitor market trends, execute trading strategies, and manage risk through these systems. Notably, the investment transaction involves risk, and the investment transactor should know the risk and take appropriate investment decisions when using any transaction system.
The prior art has the following defects:
in the prior art, when risk monitoring is carried out on system transaction data, the risk of the investment transaction cannot be monitored more accurately when a plurality of items of transaction data change at the same time and single item of transaction data do not exceed the set threshold, so that the risk of the investment transaction cannot be managed efficiently;
when the investment transaction is at risk, the investment transaction person can take some adjustment measures to adjust the investment strategy in time, and the situation of adjustment of the investment strategy cannot be known in real time because intelligent analysis cannot be performed on the situation of the investment transaction after the adjustment strategy.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The invention aims to provide a transaction data monitoring system and method of an investment transaction system, which are used for generating risk indexes by collecting investment transaction historical data and investment transaction risk data, simultaneously monitoring multiple items of transaction data through the generated risk indexes, realizing more accurate monitoring of risks of the investment transaction, prompting an investment transaction person in time when high risk conditions occur in the investment transaction, facilitating the investment transaction person to discover investment risk problems in time, performing strategy adjustment on the investment risk in time, and facilitating efficient management of the investment transaction risk so as to solve the problems in the background art.
In order to achieve the above object, the present invention provides the following technical solutions: the transaction data monitoring system of the investment transaction system comprises a data acquisition module, a comprehensive analysis module and a judgment module;
the data acquisition module acquires investment transaction historical data and investment transaction risk data and transmits the investment transaction historical data and the investment transaction risk data to the comprehensive analysis module;
the comprehensive analysis module is used for comprehensively analyzing the investment transaction historical data and the investment transaction risk data to generate a risk index and transmitting the risk index to the judging module;
the judging module is used for comparing the generated risk index with a risk index reference threshold value, generating a high-risk investment transaction signal and a low-risk investment transaction signal and transmitting the high-risk investment transaction signal and the low-risk investment transaction signal to the early warning module.
Preferably, the investment transaction history data comprises asset price volatility and bond duration, and the data acquisition module respectively marks the asset price volatility and bond duration as
And->
The investment transaction risk data comprises beta coefficients, and after acquisition, the data acquisition module marks the beta coefficients as +.>
。
Preferably, the logic for asset price volatility acquisition is as follows:
asset prices at different moments in t time are obtained, the asset prices at different moments are calibrated to be Gj, j=1, 2, 3, 4, … …, N and N are positive integers, the fluctuation rate of the asset price is obtained through the standard deviation of Gj, the larger the standard deviation of Gj is, the larger the fluctuation of the asset price is indicated, the smaller the standard deviation of Gj is, the smaller the fluctuation of the asset price is indicated, and the standard deviation of Gj is calibrated to be LS:
Preferably, the logic for bond long term acquisition is as follows:
obtaining bond long-term through calculation
The formula according to is: />
Where QS represents the number of weeks, which refers to the number of weeks the cash flow occurs per period of the bond, calculated from the bond purchase date, each period including ticket payment and principal repayment, XJ represents the cash flow, which refers to the cash flow per period including ticket payment and principal, y represents the due rate or internal rate of return of the bond, t represents the time when the cash flow occurs, calculated from the bond purchase date, and t=1, 2, 3, … …, N is a positive integer.
Preferably, the steps of obtaining the beta coefficient are as follows:
s1: collecting asset or portfolio yield data and market benchmark yield data;
s2: calculating a rate of return for each period of the asset or portfolio based on the collected data;
s3: calculating the yield of each period of the market benchmark according to the collected data;
s4: calculating covariance of asset or portfolio yield and market benchmark yield;
s5: calculating the variance of the market benchmark profitability;
s6: dividing the covariance by the variance yields the beta coefficient for the asset or portfolio.
Preferably, the comprehensive analysis module obtains the fluctuation rate of the price of the asset
Long term->
Beta coefficient>
Then, an analysis model is established, a risk index FXZx is generated, and the following formula is adopted:
Preferably, the judging module compares the generated risk index with a risk index reference threshold, if the risk index is greater than or equal to the risk index reference threshold, a high-risk investment transaction signal is generated through the judging module and transmitted to the early warning module, the early warning module sends out early warning prompt to prompt that the investment transaction risk is high, and if the risk index is less than the risk index reference threshold, a low-risk investment transaction signal is generated through the judging module and transmitted to the early warning module without sending out early warning prompt through the early warning module.
Preferably, the device further comprises a detection module;
the detection module is used for intelligently analyzing the risk index generated after the investment strategy is adjusted, and knowing the adjustment condition of the investment strategy in real time;
the detection module acquires v risk indexes FXZx to establish a data set within a period of time after the investment strategy is adjusted, and the data set is calibrated to be P
V is a positive integer, calculating the average value and the discrete degree value of v risk indexes FXZx, if the average value of the risk indexes FXZx is larger than or equal to a risk index reference threshold value, generating a signal of failure in adjustment of the investment strategy, and sending the signal to a mobile terminal to prompt an investment transactor that the strategy adjustment is unsuccessful; if the risk index FXZx average value is smaller than the risk index reference threshold value and the discrete degree value is larger than the discrete degree reference threshold value, generating an investment strategy adjustment unstable signal, sending the investment strategy adjustment unstable signal to a mobile terminal, and knowing the investment strategy adjustment unstable signal by an investment trader, wherein the occurrence of the investment strategy adjustment unstable signal indicates the investment risk after the investment strategy adjustment is good or bad and has poor stability; if the risk index FXZx average value is smaller than the risk index reference threshold value and the discrete degree value is smaller than the discrete degree reference threshold value, generating an investment strategy adjustment success signal, and sending the investment strategy adjustment success signal to the mobile terminal, prompting an investment transactor that strategy adjustment is successful, and continuously maintaining the investment mode after strategy adjustment;
the calculation formula of the discrete degree value of the risk index FXZx in the data set is as follows:
A method for monitoring transaction data of an investment transaction system, comprising the following steps:
collecting investment transaction historical data and investment transaction risk data;
comprehensively analyzing the investment transaction historical data and the investment transaction risk data to generate a risk index;
comparing the generated risk index with a risk index reference threshold value, generating a high-risk investment transaction signal and a low-risk investment transaction signal, and sending out an early warning prompt for the investment transaction generating the high-risk investment transaction signal;
and carrying out intelligent analysis on the risk index generated after the investment strategy is adjusted, and knowing the adjustment condition of the investment strategy in real time.
In the technical scheme, the invention has the technical effects and advantages that:
the invention generates the risk index by collecting the historical data of the investment transaction and the risk data of the investment transaction, monitors multiple items of transaction data simultaneously by the generated risk index, realizes more accurate monitoring of the risk of the investment transaction, and timely prompts the investment transaction person when the high risk condition occurs in the investment transaction, thereby being convenient for the investment transaction person to timely find the investment risk problem, timely carrying out strategy adjustment on the investment risk and being convenient for efficiently managing the investment transaction risk;
the invention outputs the risk index after the adjustment of the investment strategy in real time, is convenient for an investor to know the situation after the adjustment of the strategy in real time, and adopts corresponding countermeasures, thereby ensuring the stability of the investment transaction risk after the adjustment of the strategy and keeping the investment state of low risk, and greatly reducing the risk of the investment transaction.
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For a clearer description of embodiments of the present application or of the solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments described in the present invention, and that other drawings may be obtained according to these drawings for a person skilled in the art.
FIG. 1 is a schematic block diagram of a system and method for monitoring transaction data of an investment transaction system according to the present invention.
Figure 2 is a flow chart of a method for monitoring transaction data of an investment transaction system and method according to the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.
Example 1: the invention provides a transaction data monitoring system of an investment transaction system as shown in figure 1, which comprises a data acquisition module, a comprehensive analysis module and a judgment module;
the data acquisition module acquires investment transaction historical data and investment transaction risk data and transmits the investment transaction historical data and the investment transaction risk data to the comprehensive analysis module;
the investment transaction history data comprises asset price fluctuation rate and bond long term, and after acquisition, the data acquisition module respectively marks the asset price fluctuation rate and the bond long term as
And->
；
Asset price fluctuations can have the following serious impact on investment transactions:
great loss: if the asset price drops significantly, the investment trader may face a huge deficit, which may lead to significant shrinkage of the investment funds of the investment trader, and may even exceed its bearing capacity, causing financial dilemma;
the investment transactant is panicked and emotionally out of control: the large fluctuation in asset price may cause panic and emotional runaway for the investment trader, who may impulsively make wrong decisions due to the severe fluctuation in the market, resulting in further losses;
funding problem: when the price of an asset fluctuates greatly, the liquidity of the market may be affected, and an investment trader may face the problem that it is difficult to buy or sell the asset, resulting in difficulty in trade execution;
lever explosion risk: if an investment transactor uses a lever to conduct transaction, i.e. borrow to conduct investment, the large fluctuation of the price of the asset can lead to the risk of lever explosion, and when the price of the asset drops, the investment transactor can not repay the borrow, resulting in default risk and further loss;
investment strategy failure: the large fluctuation of the asset price may lead to the failure of the original investment strategy of the investment transactor, the expectation and assumption of the investment transactor may not cope with the severe fluctuation of the market, resulting in the failure of the investment strategy to generate the expected benefits;
therefore, the amplitude of the price fluctuation of the asset is obtained, and the risk condition of the investment transaction can be known;
the logic for asset price volatility acquisition is as follows:
asset prices at different moments in t time are obtained, the asset prices at different moments are calibrated to be Gj, j=1, 2, 3, 4, … …, N and N are positive integers, the fluctuation rate of the asset price is obtained through the standard deviation of Gj, the larger the standard deviation of Gj is, the larger the fluctuation of the asset price is indicated, the smaller the standard deviation of Gj is, the smaller the fluctuation of the asset price is indicated, and the standard deviation of Gj is calibrated to be LS:
The long term bond may have the following serious impact on investment transactions:
interest rate risk: long-term bond is an indicator of the sensitivity of bond price to the change in interest rate, when market interest rate changes, the longer-term bond price fluctuation range is larger, which may lead to investment traders facing larger interest rate risks, if market interest rate increases, bond price decreases, investment traders may face losses or fail to obtain expected returns as expected;
heavy investment risk: the long-term bond of the bond is exposed to the risk of re-investment after expiration, and after the bond expires, the investment transactor needs to re-invest principal and interest, but at this time, the market interest rate may have changed, and if the market interest rate decreases, the investment transactor may not be able to obtain the same high rate of return as the original bond again, resulting in a decrease in the return on investment;
market mobility risk: long bond bonds are more susceptible to insufficient market liquidity, and when market liquidity decreases, investment traders may face problems of difficulty in buying or selling bonds, which may lead to difficulty in executing the trade and adverse fluctuations in price;
credit risk: long-term bonds often have a higher credit risk, and due to their longer term, these bonds are more susceptible to deterioration in the credit status of the liaison, and if the liaison cannot pay principal and interest on time, the investment transacter may be exposed to a default risk, resulting in losses;
investment portfolio risk: long-term bond is an important index for evaluating the price fluctuation risk of bonds, in an investment portfolio, the long-term bond of the bonds can have a great influence on the fluctuation of the whole investment portfolio, and if the long-term bond price of the bonds fluctuates greatly, the value of the whole investment portfolio can also fluctuate, so that the investment portfolio risk is brought;
therefore, the long-term bond is obtained, and the risk condition of the investment transaction can be known;
the logic for bond long term acquisition is as follows:
macaulay duration (Macaulay Duration) is the most commonly used bond duration calculation method, which represents a weighted average duration of bond cash flow, and the bond duration is obtained by calculation of Macaulay duration
The formula according to is:
wherein QS represents an amount of time, which indicates an amount of time that a cash flow occurs per period of the bond, calculated from a bond purchase date, each period including ticket payment and principal repayment, XJ represents a cash flow, which indicates a cash flow per period including ticket payment and principal, y represents an expiration rate or an internal rate of return of the bond, t represents a time when the cash flow occurs, calculated from the bond purchase date, and t=1, 2, 3, … …, N is a positive integer;
the investment transaction risk data comprises beta coefficients, and after acquisition, the data acquisition module calibrates the beta coefficients to be
；
In an investment transaction, the beta coefficient is an index that measures the overall fluctuation of an asset or portfolio with respect to the market, and when the beta coefficient is low, this means that the fluctuation of the asset or portfolio is relatively low, and the fluctuation correlation with the market overall is weak, which may have the following serious effects on the investment transaction:
lower revenue potential: when an asset or portfolio with a lower beta coefficient is on the market, its return may be lower than the full rise of the market, which means that the investment trader may miss the opportunity for the market to rise, resulting in lower return potential;
restriction diversification: a lower beta coefficient may mean that the volatility of an asset or portfolio is less relevant to the volatility of the market as a whole and less relevant to other assets or portfolios, which may limit the ability of investment traders to make diverse investments, as a lower beta coefficient means that the asset or portfolio may not provide adequate risk avoidance when the market falls;
highly dependent on specific factors: a lower beta coefficient may indicate that the volatility of an asset or portfolio is primarily affected by certain factors, such as a particular industry, company, or other non-market factor, which makes the asset or portfolio more sensitive to these factors, increasing the exposure to a particular risk, which may be at greater risk if these factors are changed or are adversely affected;
risk in highly fluctuating markets: in the case of higher market volatility, the lower beta coefficient may result in relatively lower volatility for the asset or portfolio, failing to adequately reflect market volatility, which may make it difficult for investment traders to handle when the market fluctuates drastically, failing to effectively reduce risk;
therefore, the beta coefficient in the investment transaction is obtained, and the risk condition of the investment transaction can be known;
the beta coefficient is obtained as follows:
s1: collecting asset or portfolio yield data and market benchmark yield data (time periods are the same and have a correspondence);
s2: calculating the rate of return of the asset or portfolio for each period based on the collected data (rate of return may be calculated by log-difference or percentage change of price);
s3: calculating the yield of each period of the market benchmark according to the collected data;
s4: calculating covariance of asset or portfolio yield to market benchmark yield (covariance measures linear relationship between two variables and their co-variability);
s5: calculating the variance of the market benchmark profitability (the variance measures the degree of variation of the market benchmark profitability);
s6: dividing the covariance by the variance to obtain beta coefficients for the asset or portfolio;
the comprehensive analysis module is used for comprehensively analyzing the investment transaction historical data and the investment transaction risk data to generate a risk index and transmitting the risk index to the judging module;
the comprehensive analysis module obtains the fluctuation rate of the price of the asset
Long term->
Beta coefficient>
Then, an analysis model is established, a risk index FXZx is generated, and the following formula is adopted:
the formula shows that the larger the asset price fluctuation rate is, the longer the bond is in a long period, the larger the beta coefficient is, namely the larger the expression value of the risk index FXZx is, the larger the risk of the investment trade is, the smaller the asset price fluctuation rate is, the shorter the bond is in a long period, the smaller the beta coefficient is, namely the smaller the expression value of the risk index FXZx is, and the smaller the risk of the investment trade is;
the judging module is used for comparing the generated risk index with a risk index reference threshold value, generating a high-risk investment transaction signal and a low-risk investment transaction signal and transmitting the high-risk investment transaction signal and the low-risk investment transaction signal to the early warning module;
the judging module compares the generated risk index with a risk index reference threshold, if the risk index is larger than or equal to the risk index reference threshold, the high-risk investment transaction signal is generated through the judging module and transmitted to the early warning module, the early warning module sends out early warning prompt to prompt that the investment transaction risk is high, so that an investment transactor can find out the investment risk problem in time, strategy adjustment is carried out on the investment risk in time, if the risk index is smaller than the risk index reference threshold, the low-risk investment transaction signal is generated through the judging module and transmitted to the early warning module, and the early warning prompt is not sent out through the early warning module;
the invention generates the risk index by collecting the historical data of the investment transaction and the risk data of the investment transaction, monitors multiple items of transaction data simultaneously by the generated risk index, realizes more accurate monitoring of the risk of the investment transaction, and timely prompts the investment transaction person when the high risk condition occurs in the investment transaction, thereby being convenient for the investment transaction person to timely find the investment risk problem, timely carrying out strategy adjustment on the investment risk and being convenient for efficiently managing the investment transaction risk;
the detection module is used for intelligently analyzing the risk index generated after the investment strategy is adjusted, and knowing the adjustment condition of the investment strategy in real time;
the detection module acquires v risk indexes FXZx to establish a data set within a period of time after the investment strategy is adjusted, and the data set is calibrated to be P
V is a positive integer, calculating the average value and the discrete degree value of v risk indexes FXZx, if the average value of the risk indexes FXZx is larger than or equal to a risk index reference threshold value, generating a signal of failure in adjustment of the investment strategy, and sending the signal to a mobile terminal to prompt an investment transactor that the strategy adjustment is unsuccessful; if the risk index FXZx average value is smaller than the risk index reference threshold value and the discrete degree value is larger than the discrete degree reference threshold value, generating an investment strategy adjustment unstable signal, sending the investment strategy adjustment unstable signal to a mobile terminal, and knowing by an investment trader, indicating that the investment risk after the investment strategy adjustment is good or bad when the investment strategy adjustment is present, wherein the stability is poor, the investment strategy needs to be further adjusted, and the investment trade risk after the strategy adjustment is ensured to be stable and the investment state of low risk is kept; if the risk index FXZx average value is smaller than the risk index reference threshold value and the discrete degree value is smaller than the discrete degree reference threshold value, generating an investment strategy adjustmentThe whole success signal is sent to the mobile terminal to prompt the investment transactor that the strategy adjustment is successful, and the investment mode after the strategy adjustment is continuously maintained, so that the low-risk transaction investment can be realized;
the calculation formula of the discrete degree value of the risk index FXZx in the data set is as follows:
the invention outputs the risk index after the adjustment of the investment strategy in real time, is convenient for an investor to know the situation after the adjustment of the strategy in real time, and adopts corresponding countermeasures, thereby ensuring the stability of the investment transaction risk after the adjustment of the strategy and keeping the investment state of low risk, and greatly reducing the risk of the investment transaction.
Example 2: the invention provides a method for monitoring transaction data of an investment transaction system as shown in figure 2, which comprises the following steps:
collecting investment transaction historical data and investment transaction risk data;
comprehensively analyzing the investment transaction historical data and the investment transaction risk data to generate a risk index;
comparing the generated risk index with a risk index reference threshold value, generating a high-risk investment transaction signal and a low-risk investment transaction signal, and sending out an early warning prompt for the investment transaction generating the high-risk investment transaction signal;
intelligent analysis is carried out on the risk index generated after the investment strategy is adjusted, and the adjustment condition of the investment strategy is known in real time;
the method for monitoring transaction data of an investment transaction system is realized by the transaction data monitoring system of the investment transaction system, and the specific method and the flow of the method for monitoring transaction data of the investment transaction system are detailed in the embodiment of the transaction data monitoring system of the investment transaction system, and are not repeated herein.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (9)
1. The transaction data monitoring system of the investment transaction system is characterized by comprising a data acquisition module, a comprehensive analysis module and a judgment module;
the data acquisition module acquires investment transaction historical data and investment transaction risk data and transmits the investment transaction historical data and the investment transaction risk data to the comprehensive analysis module;
the comprehensive analysis module is used for comprehensively analyzing the investment transaction historical data and the investment transaction risk data to generate a risk index and transmitting the risk index to the judging module;
the judging module is used for comparing the generated risk index with a risk index reference threshold value, generating a high-risk investment transaction signal and a low-risk investment transaction signal and transmitting the high-risk investment transaction signal and the low-risk investment transaction signal to the early warning module.
2. The system of claim 1, wherein the historical data of investment transactions includes asset price volatility and bond duration, and the data collection module is configured to calibrate the asset price volatility and bond duration to respectively
And->
The investment transaction risk data comprises beta coefficients, and after acquisition, the data acquisition module marks the beta coefficients as +.>
。
3. A trading data monitoring system in accordance with claim 2, wherein the logic for acquiring the price volatility of the asset is as follows:
asset prices at different moments in t time are obtained, the asset prices at different moments are calibrated to be Gj, j=1, 2, 3, 4, … …, N and N are positive integers, the fluctuation rate of the asset price is obtained through the standard deviation of Gj, the larger the standard deviation of Gj is, the larger the fluctuation of the asset price is indicated, the smaller the standard deviation of Gj is, the smaller the fluctuation of the asset price is indicated, and the standard deviation of Gj is calibrated to be LS:
4. The system for monitoring transaction data of an investment transaction system according to claim 2, wherein the logic for long term bond acquisition is as follows:
obtaining bond long-term through calculation
The formula according to is: />
Where QS represents the number of weeks, which refers to the number of weeks the cash flow occurs per period of the bond, calculated from the bond purchase date, each period including ticket payment and principal repayment, XJ represents the cash flow, which refers to the cash flow per period including ticket payment and principal, y represents the due rate or internal rate of return of the bond, t represents the time when the cash flow occurs, calculated from the bond purchase date, and t=1, 2, 3, … …, N is a positive integer.
5. A trading data monitoring system in accordance with claim 2, wherein the step of obtaining the beta coefficient is as follows:
s1: collecting asset or portfolio yield data and market benchmark yield data;
s2: calculating a rate of return for each period of the asset or portfolio based on the collected data;
s3: calculating the yield of each period of the market benchmark according to the collected data;
s4: calculating covariance of asset or portfolio yield and market benchmark yield;
s5: calculating the variance of the market benchmark profitability;
s6: dividing the covariance by the variance yields the beta coefficient for the asset or portfolio.
6. The system for monitoring transaction data of an investment transaction system according to claim 2, wherein the integrated analysis module obtains asset price volatility
Long term->
Beta coefficient>
Then, an analysis model is established, a risk index FXZx is generated, and the following formula is adopted:
7. The system of claim 6, wherein the judgment module compares the risk index generated with a risk index reference threshold, if the risk index is greater than or equal to the risk index reference threshold, the judgment module generates a high-risk investment transaction signal, which is transmitted to the early warning module, the early warning module sends out an early warning prompt to indicate that the risk of the investment transaction is high, and if the risk index is less than the risk index reference threshold, the judgment module generates a low-risk investment transaction signal, which is transmitted to the early warning module, and the early warning module does not send out the early warning prompt.
8. The system for monitoring transaction data of an investment transaction system according to claim 7, further comprising a detection module;
the detection module is used for intelligently analyzing the risk index generated after the investment strategy is adjusted, and knowing the adjustment condition of the investment strategy in real time;
the detection module acquires v risk indexes FXZx to establish a data set within a period of time after the investment strategy is adjusted, and the data set is calibrated to be P
V is a positive integer, calculating the average value and the discrete degree value of v risk indexes FXZx, if the average value of the risk indexes FXZx is larger than or equal to a risk index reference threshold value, generating a signal of failure in adjustment of the investment strategy, and sending the signal to a mobile terminal to prompt an investment transactor that the strategy adjustment is unsuccessful; if the risk index FXZx average value is smaller than the risk index reference threshold value and the discrete degree value is larger than the discrete degree reference threshold value, generating an investment strategy adjustment unstable signal, sending the investment strategy adjustment unstable signal to a mobile terminal, and knowing the investment strategy adjustment unstable signal by an investment trader, wherein the occurrence of the investment strategy adjustment unstable signal indicates the investment risk after the investment strategy adjustment is good or bad and has poor stability; if the risk index FXZx average value is smaller than the risk index reference threshold value and the discrete degree value is smaller than the discrete degree reference threshold value, generating an investment strategy adjustment success signal, and sending the investment strategy adjustment success signal to the mobile terminal, prompting an investment transactor that strategy adjustment is successful, and continuously maintaining the investment mode after strategy adjustment;
the calculation formula of the discrete degree value of the risk index FXZx in the data set is as follows:
9. A method for monitoring transaction data of an investment transaction system, which is realized by the transaction data monitoring system of the investment transaction system according to any one of claims 1 to 8, and is characterized by comprising the following steps:
collecting investment transaction historical data and investment transaction risk data;
comprehensively analyzing the investment transaction historical data and the investment transaction risk data to generate a risk index;
comparing the generated risk index with a risk index reference threshold value, generating a high-risk investment transaction signal and a low-risk investment transaction signal, and sending out an early warning prompt for the investment transaction generating the high-risk investment transaction signal;
and carrying out intelligent analysis on the risk index generated after the investment strategy is adjusted, and knowing the adjustment condition of the investment strategy in real time.
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| CN118172176A (en) * | 2024-05-14 | 2024-06-11 | 青岛场外市场清算中心有限公司 | Financial risk analysis method and system based on blockchain |
| CN118312572A (en) * | 2024-06-07 | 2024-07-09 | 无锡锡商银行股份有限公司 | Real-time data center-based processing method |
| CN119228547A (en) * | 2024-09-24 | 2024-12-31 | 上海市大数据中心 | A financial data intelligent management system and method based on cloud platform |
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| CN114037536A (en) * | 2021-10-11 | 2022-02-11 | 深圳职业技术学院 | Stock Intelligent Investment System |
| CN116090820A (en) * | 2023-01-30 | 2023-05-09 | 苏州汇千数据科技有限公司 | Wind control parameter intelligent monitoring analysis system applied to high-frequency transaction scene |
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| US20030130917A1 (en) * | 2001-04-27 | 2003-07-10 | Andrea Crovetto | Computer system for determining the risk index of a financial instrument and relevant method |
| CN114037536A (en) * | 2021-10-11 | 2022-02-11 | 深圳职业技术学院 | Stock Intelligent Investment System |
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| CN118172176A (en) * | 2024-05-14 | 2024-06-11 | 青岛场外市场清算中心有限公司 | Financial risk analysis method and system based on blockchain |
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| CN119228547A (en) * | 2024-09-24 | 2024-12-31 | 上海市大数据中心 | A financial data intelligent management system and method based on cloud platform |
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