Investment risk assessment method and system based on artificial intelligence

Abstract

The invention discloses an artificial intelligence-based investment risk assessment method and system, and relates to the technical field of investment risk assessment, and the method comprises the steps: obtaining the number of occurrences of each investment product entry on a social media platform in the recent month, the number of occurrences of positive vocabularies, and the number of occurrences of negative vocabularies; calculating the predicted social contact popularity of each investment product in the next month; obtaining the transaction volume, the transaction price and the increase and decrease amplitude of each investment product in the next month from the official website of the exchange, and calculating the predicted transaction popularity of each investment product in the next month; calculating an investment risk coefficient of each investment product, when the investment risk coefficient of the investment product is less than 0, marking the investment product as a risk investment product, when the investment risk coefficient of the investment product is not less than 0, calculating a second investment risk coefficient of the investment product, and if the second investment risk coefficient of the investment product is not less than 0, marking the investment product as a risk investment product; and if yes, outputting the investment product to be recommended. Relatively robust investment products can be screened out, and decision support is provided for investors.

Description

Technical Field

[0001] The present invention relates to the technical field of investment risk assessment, and in particular to an investment risk assessment method and system based on artificial intelligence. Background Art

[0002] In the field of investment, risk assessment is a crucial link. Traditional investment risk assessment methods often rely on historical data and manual experience. These methods have problems such as strong subjectivity and limited timeliness, and are difficult to meet the needs of modern complex financial markets. With the rapid development of artificial intelligence technology, its application in the field of financial investment has become increasingly widespread, providing new solutions for investment risk assessment. In recent years, the application of artificial intelligence in the financial field has achieved remarkable results. By using technologies such as big data, machine learning, and natural language processing, artificial intelligence can analyze and process massive amounts of data, thereby providing more accurate and efficient risk assessment results. These technologies can not only help investors discover potential risks in a timely manner, but also provide investors with more comprehensive decision-making support.

[0003] In the Chinese invention application with application publication number CN113408873A, a method for evaluating investment risk based on big data and artificial intelligence technology is disclosed, including S1. First, investment market data is collected through big data, a risk investment evaluation model is established, and risk investment analysis is provided to users. S2. Users register as investment platform users and fill in basic investment information. The present invention monitors investment projects in real time through the investment risk evaluation model, sets risk warning levels, monitors and analyzes them according to cycles, and when investments encounter risks, timely analyzes risks through big data, evaluates risk levels, distinguishes controllable risks from uncontrollable risks, and determines the fluctuation range between risks and expectations. Users can grasp risks more quickly, understand the specific levels of risks and the fluctuation range, so that users can understand risk warnings in a timely and intuitive manner. When warnings appear, reasonable measures are given for users to refer to and reduce investment losses.

[0004] In the above invention application, when the investment encounters risks, the risk level is assessed in a timely manner through big data analysis. The risk analysis is conducted after the investment encounters risks, which means that the decision is based on events that have already occurred, rather than preventive. This lag may result in the inability to take effective measures in a timely manner to mitigate or avoid losses caused by risks. More resources may need to be invested to cope with it, including funds, manpower and time. This increases the total cost of investment and may reduce the return on investment.

[0005] To this end, the present invention provides an investment risk assessment method and system based on artificial intelligence. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides an investment risk assessment method and system based on artificial intelligence. The present invention obtains the predicted social popularity of each investment product in the next month. And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output for recommendation, which can screen out relatively stable investment products, provide decision support for investors, reduce investment risks, and thus solve the technical problems recorded in the background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: an investment risk assessment method based on artificial intelligence, comprising the following steps: Get the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month ; Obtain the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month ; Get the predicted social popularity of each investment product next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

[0008] Furthermore, we use keyword search and data analysis tools on social media platforms (such as Weibo, WeChat, Douyin, etc.) to obtain the number of times each investment product entry appears on the social media platform in the past month. , and extract the number of occurrences of positive words that appear in the same sentence as each investment product term on the social media platform and the number of occurrences of negative words .

[0009] Among them, positive words include "good", "excellent", "satisfied", "making money", "profitable", etc., while negative words include "bad", "terrible", "unsatisfied", "losing money", "losing money", etc.

[0010] Furthermore, the number of times each investment product entry appears on the social media platform in the past month is obtained , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product :

[0011] in, i Indicates the number of each investment product entry, j The date number indicating the date on which the term or word appeared on the social media platform. j =1, 2, …, 30.

[0012] Furthermore, obtain the social popularity of each investment product , calculate the social popularity change rate of each investment product in the past month :

[0013] Corresponding social popularity change rate of each investment product The calculation formula is as above.

[0014] Furthermore, obtain the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month :

[0015] in, Indicates the social popularity of each investment product on the most recent date.

[0016] Furthermore, the trading volume of each investment product in the past month is obtained from the official website of the exchange. , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product :

[0017] The corresponding trading popularity of each investment product The calculation formula is as above.

[0018] Furthermore, obtain the trading popularity of each investment product , calculate the transaction popularity change rate of each investment product in the past month :

[0019] Corresponding change rate of transaction popularity of each investment product The calculation formula is as above.

[0020] Furthermore, obtain the transaction popularity change rate of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month :

[0021] in, Indicates the trading popularity of each investment product on the most recent date.

[0022] Furthermore, obtain the predicted social popularity of each investment product for the next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product :

[0023] When the investment risk factor of the investment product When it is less than 0, the investment product is marked as a venture capital product.

[0024] Furthermore, when the investment risk factor of the investment product When it is not less than 0, obtain the investment risk coefficient of all investment products of the company corresponding to the investment product, and calculate the mean value and record it as the auxiliary risk coefficient of the investment product. , based on the investment risk factor and auxiliary risk factor , calculate the second investment risk coefficient of the investment product :

[0025] If the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

[0026] An investment risk assessment system based on artificial intelligence, comprising: Social heat analysis module, to obtain the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month ; The trading heat analysis module obtains the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month ; Investment risk analysis module, obtains the predicted social popularity of each investment product in the next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

[0027] The present invention provides an investment risk assessment method and system based on artificial intelligence, which has the following beneficial effects: 1. Obtain the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month , which can reflect the trend and speed of product popularity, and can more accurately grasp market dynamics and changes in public sentiment.

[0028] This helps in assessing the investment risks of various investment products.

[0029] 2. Obtain the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month , you can identify in advance those investment products that may face declining trading volumes, falling prices, or increased volatility.

[0030] 3. Obtain the predicted social popularity of each investment product for the next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output for recommendation, which can screen out relatively stable investment products, provide decision-making support for investors, and reduce investment risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic diagram of a flow chart of an investment risk assessment method based on artificial intelligence according to the present invention; Figure 2 The present invention is a schematic diagram of the structure of an investment risk assessment system based on artificial intelligence. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] See also Figure 1 The present invention provides an investment risk assessment method based on artificial intelligence, comprising the following steps: Step 1: Obtain the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month .

[0034] The step 1 includes the following contents: Step 101: Based on keyword searches and data analysis tools on social media platforms (such as Weibo, WeChat, TikTok, etc.), obtain the number of times each investment product entry appears on the social media platform in the past month. , and extract the number of occurrences of positive words that appear in the same sentence as each investment product term on the social media platform and the number of occurrences of negative words .

[0035] Among them, positive words include "good", "excellent", "satisfied", "making money", "profitable", etc., while negative words include "bad", "terrible", "unsatisfied", "losing money", "losing money", etc.

[0036] Step 102: Obtain the number of times each investment product entry appears on the social media platform in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product :

[0037] in, i Indicates the number of each investment product entry, j The date number indicating the date on which the term or word appeared on the social media platform. j =1, 2, …, 30.

[0038] Step 103: Obtain the social popularity of each investment product , calculate the social popularity change rate of each investment product in the past month :

[0039] Corresponding social popularity change rate of each investment product The calculation formula is as above.

[0040] Step 104: Obtain the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month :

[0041] in, Indicates the social popularity of each investment product on the most recent date.

[0042] When using, combine the contents in step 101 to step 104: Get the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month , which can reflect the trend and speed of product popularity, and can more accurately grasp market dynamics and changes in public sentiment.

[0043] This helps in assessing the investment risks of various investment products.

[0044] Step 2: Obtain the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month .

[0045] The step 2 includes the following contents: Step 201: Obtain the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product :

[0046] The corresponding trading popularity of each investment product The calculation formula is as above.

[0047] Step 202: Obtain the transaction popularity of each investment product , calculate the transaction popularity change rate of each investment product in the past month :

[0048] Corresponding change rate of transaction popularity of each investment product The calculation formula is as above.

[0049] Step 203: Obtain the transaction popularity change rate of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month :

[0050] in, Indicates the trading popularity of each investment product on the most recent date.

[0051] When used, combine the contents in step 201 to step 203: Obtain the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month , you can identify in advance those investment products that may face declining trading volumes, falling prices, or increased volatility.

[0052] Step 3: Obtain the predicted social popularity of each investment product for the next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

[0053] The step three includes the following contents: Step 301: Obtain the predicted social popularity of each investment product for the next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product :

[0054] When the investment risk factor of the investment product When it is less than 0, the investment product is marked as a venture capital product.

[0055] Step 302: When the investment risk factor of the investment product When it is not less than 0, obtain the investment risk coefficient of all investment products of the company corresponding to the investment product, and calculate the mean value and record it as the auxiliary risk coefficient of the investment product. , based on the investment risk factor and auxiliary risk factor , calculate the second investment risk coefficient of the investment product :

[0056] If the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

[0057] When used, combine the contents in step 301 and step 302: Get the predicted social popularity of each investment product next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output for recommendation, which can screen out relatively stable investment products, provide decision-making support for investors and reduce investment risks.

[0058] See also Figure 2 The present invention provides an investment risk assessment system based on artificial intelligence, comprising: Social heat analysis module, to obtain the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month .

[0059] The trading heat analysis module obtains the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month .

[0060] Investment risk analysis module, obtains the predicted social popularity of each investment product in the next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

[0061] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0062] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0063] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An investment risk assessment method based on artificial intelligence, characterized in that: The steps include: Get the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month ; Obtain the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month ; Get the predicted social popularity of each investment product next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

2. The investment risk assessment method based on artificial intelligence according to claim 1, characterized in that: Get the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product : in, i Indicates the number of each investment product entry, j The date number indicating the date on which the term or word appeared on the social media platform. j =1, 2, …, 30.

3. The investment risk assessment method based on artificial intelligence according to claim 2, characterized in that: Get the social popularity of each investment product , calculate the social popularity change rate of each investment product in the past month : Corresponding social popularity change rate of each investment product The calculation formula is as above.

4. The investment risk assessment method based on artificial intelligence according to claim 3 is characterized in that: Get the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month : in, Indicates the social popularity of each investment product on the most recent date.

5. The investment risk assessment method based on artificial intelligence according to claim 4 is characterized in that: Obtain the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product : The corresponding trading popularity of each investment product The calculation formula is as above.

6. The investment risk assessment method based on artificial intelligence according to claim 5, characterized in that: Get the trading popularity of each investment product , calculate the transaction popularity change rate of each investment product in the past month : Corresponding change rate of transaction popularity of each investment product The calculation formula is as above.

7. The investment risk assessment method based on artificial intelligence according to claim 6 is characterized in that: Get the transaction popularity change rate of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month : in, Indicates the trading popularity of each investment product on the most recent date.

8. The investment risk assessment method based on artificial intelligence according to claim 7 is characterized in that: Get the predicted social popularity of each investment product next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product : When the investment risk factor of the investment product When it is less than 0, the investment product is marked as a venture capital product.

9. The investment risk assessment method based on artificial intelligence according to claim 8, characterized in that: When the investment risk factor of the investment product When it is not less than 0, obtain the investment risk coefficient of all investment products of the company corresponding to the investment product, and calculate the mean value and record it as the auxiliary risk coefficient of the investment product. , based on the investment risk factor and auxiliary risk factor , calculate the second investment risk coefficient of the investment product : If the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

10. An investment risk assessment system based on artificial intelligence, used to implement the method described in any one of claims 1 to 9, characterized in that: include: Social heat analysis module, to obtain the number of times each investment product entry appears on social media platforms in the past month , the number of occurrences of active words and the number of occurrences of negative words , calculate the social popularity of each investment product , based on the social popularity change rate of each investment product in the past month and the social popularity of each investment product , calculate the predicted social popularity of each investment product next month ; The trading heat analysis module obtains the trading volume of each investment product in the past month from the official website of the exchange , Transaction Price , Rise / Fall , calculate the trading popularity of each investment product , based on the change rate of trading popularity of each investment product in the past month and the trading popularity of various investment products , calculate the predicted trading popularity of each investment product in the next month ; Investment risk analysis module, obtains the predicted social popularity of each investment product in the next month And the predicted trading volume for next month , calculate the investment risk coefficient of each investment product , when the investment risk factor of the investment product When the investment risk coefficient of the investment product is less than 0, the investment product is marked as a risky investment product. When it is not less than 0, according to the investment risk coefficient and auxiliary risk factor , calculate the second investment risk coefficient of the investment product , if the second investment risk factor of the investment product When it is less than 0, the investment product is marked as a risky investment product. If it is not less than 0, the investment product will be output as a recommendation.

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