Investment management system based on self-owned fund analysis

Abstract

The invention relates to the technical field of fund analysis, in particular to an investment management system based on self-owned fund analysis. Comprising a fund data list analysis module used for extracting own fund data, flowing fund data and non-flowing fund data in a fund data list, a user investment preference analysis module used for analyzing user investment preferences, an error information feedback module and an investment project analysis module. The method comprises the following steps: calculating actual own fund data of a user through a fund data list analysis module, judging whether the fund data in a fund data list is wrong or not according to a fund data threshold interval, and when the fund data is wrong, determining by a user investment preference analysis module according to the proportion condition of flowing fund data and non-flowing fund data in the actual own fund data; and according to the investment preference of the current user, adjusting the wrong fund data list of the current user according to the fund data list in the history corresponding to the investment preference.

Description

Technical Field

[0001] The present invention relates to the technical field of fund analysis, and in particular to an investment management system based on own fund analysis. Background Art

[0002] The usual operation process of the investment management system is that the investment user first fills in the capital data list, and then analyzes the own funds in the list. At this time, the economic strength and capital stability of the investment user are determined through the distribution of liquid funds and non-liquid funds in the capital data list, and then suitable investment projects are recommended to the investment user; However, before the existing investment management system analyzes the own funds data, since the investment portfolios of investment users are often complex and diverse, involving multiple financial institutions and different types of asset data, such as stocks, funds, bonds, various financial products, and physical assets, etc., over time, it may be difficult for investors to accurately remember the detailed information of each asset, including its exact amount, purchase time, relevant terms, etc., which may lead to errors in filling out some fund data lists. Because when recommending investment projects to current users, it is necessary to rely on accurate current own funds data. Once the data is wrong, the recommendation results will inevitably be inaccurate; At the same time, when some investment users come into contact with a new investment management system, since investment decisions are related to the investment users' capital security and returns, they hope to ensure that the investment projects recommended by the system are truly based on reasonable analysis and accurate data processing. Therefore, in order to test whether the investment projects recommended by the investment management system are accurate, they will deliberately fill in incorrect capital data. At this time, if the incorrect capital data cannot be fed back to the investment users, it will reduce the users' trust in the professionalism of the system. In view of this, we propose an investment management system based on own capital analysis. Summary of the invention

[0003] The purpose of the present invention is to solve the problem that when an investment user fills in a fund data list, the wrong fund data cannot be adjusted and the problem that intentionally wrong fund data cannot be identified.

[0004] To achieve the above-mentioned purpose, the present invention provides an investment management system that can identify the filled-in fund data through the fund data list analysis module and the error information feedback module, judge whether the user intentionally fills in the wrong fund data information, and feedback to the investment user's own fund analysis, including a fund data list analysis module, a user investment preference analysis module, an error information feedback module and an investment project analysis module; The fund data list analysis module extracts the own fund data, current fund data and non-current fund data in the fund data list filled in by the user, and sets the fund data threshold interval; If the actual own funds data is within the fund data threshold range, the output user-provided own funds data is the user's actual own funds data; otherwise, the output fund data is filled in incorrectly; The user investment preference analysis module senses the signal of incorrect fund data filling, analyzes the user's investment preference, calls out multiple groups of fund data with the same investment preference as the current user according to the user's investment preference, and adjusts the incorrectly filled fund data according to the fund data with the highest similarity; The error information feedback module adjusts the fund data threshold interval according to the user's investment preference, and determines again whether the adjusted fund data is within the fund data threshold interval. If it is, the adjusted fund data is output as the user's fund data. Otherwise, it is determined that the fund data filled in by the user is wrong. The investment project analysis module senses multiple groups of fund data with the same investment preference as the current user, selects the investment preferences corresponding to the top ten percent of users, and provides suitable investment projects for the current user.

[0005] As a further improvement of the technical solution, the steps of extracting the own funds data, liquid funds data and non-liquid funds data from the funds data list provided by the user by the funds data list analysis module are as follows: First, mark the table names corresponding to own funds, current funds, and non-current funds; Then, the marked table names are compared one by one with the table names in the fund data list provided by the user by using the direct comparison method; After the comparison is completed, the fund data corresponding to the table names of own funds, current funds and non-current funds are retrieved, and the own funds data, current funds data and non-current funds data in the fund data list are extracted.

[0006] As a further improvement of the technical solution, the steps for the fund data list analysis module to determine whether the actual own fund data is within the fund data threshold range are as follows: Receive own funds data in the funds data list , actual own funds data and funding data threshold range ; Calculate the actual own funds data range , ; like , then the own funds data in the output fund data list is the user's actual own funds data; like and When the current funds data and non-current funds data in the output funds data list are filled in incorrectly.

[0007] As a further improvement of the technical solution, the steps of analyzing the user's investment preference in the user investment preference analysis module are as follows: Receive liquidity data from historical user fund data respectively , Non-current Funds Data and actual own funds data ; ; ; in, and Liquidity data and illiquid funds data In actual own funds data The proportion of , it indicates that the user is a robust user; , it indicates that the user is an aggressive user.

[0008] As a further improvement of the technical solution, the steps of calculating the similarity between the historical and current corresponding liquid funds data and non-liquid funds data in the user investment preference analysis module are as follows: Sense error signals of filling in current fund data and non-current fund data in the fund data list analysis module; Receive current user investment preferences, historical user investment preferences, historical liquid funds data, and historical illiquid funds data; Retrieve the current and current user's corresponding liquid fund data and non-liquid fund data; The similarity between multiple groups of historical liquid funds data, historical non-liquid funds data and the current user's liquid funds data and non-liquid funds data is calculated respectively. The calculation formula is as follows: ; in, Indicates the similarity between historical liquid funds data, historical non-liquid funds data and the current user's liquid funds data, non-liquid funds data, Indicates the number of users with the same investment preferences as the current user. The current user's liquidity data, It is the current user's non-liquidity data. For the Historical user liquidity data, For the Historical user illiquid funds data; like , then the output The historical liquid funds data and historical non-liquid funds data corresponding to the historical customers are most similar to the liquid funds data and non-liquid funds data corresponding to the current user.

[0009] As a further improvement of the technical solution, the steps of adjusting the incorrectly filled capital data by the user investment preference analysis module are as follows: Receive the fund data threshold interval in the fund data list analysis module ; Receive current user liquidity data , Non-current Funds Data and historical user liquidity data , Non-current Funds Data ; The bank deposit balance in the historical liquidity data is , the bank deposit balance in the current user's liquidity data is ; like , , then the bank deposit balance of the current user's working capital data is output to be filled in incorrectly, and the bank deposit balance in the historical working capital data is adjusted to the bank deposit balance of the current user's working capital data; The bank deposit balance in the historical liquidity data is , the bank deposit balance in the current user's liquidity data is ; like , , then the bank deposit balance of the current user's non-liquidity data is outputted with errors, and the bank deposit balance in the historical non-liquidity data is adjusted to the bank deposit balance of the current user's non-liquidity data.

[0010] As a further improvement of the technical solution, the steps of adjusting the threshold interval of fund data by the error information feedback module are as follows: Receive the fund data threshold interval in the fund data list analysis module , receiving the current user investment preference analyzed in the user investment preference analysis module; If the current user's investment preference is aggressive, the fund data threshold interval will be increased. for: ; If the current user's investment preference is a conservative user, the fund data threshold range is lowered for: .

[0011] As a further improvement of the technical solution, the steps of the investment project analysis module providing a suitable investment project for the current user are as follows: Receive the similarity calculated in the user investment preference analysis module ; Retrieving historical investment users corresponding to the similarity, and then labeling the historical investment users according to the similarity; like ,but The corresponding historical investment user is , The corresponding historical investment user is , and so on, all historical investment users are labeled ; And calculate the users corresponding to the top 10% of historical users, ,in Indicates the number of historical users; The investment preferences of the top ten percent of users are retrieved for recommendation to current investment users.

[0012] Compared with the prior art, the present invention has the following beneficial effects: In the investment management system based on own fund analysis, the actual own fund data of the user is calculated through the fund data list analysis module, and then the fund data threshold interval is used to determine whether the fund data in the fund data list is wrong. If it is wrong, the user investment preference analysis module determines the current user's investment preference according to the proportion of liquid fund data and non-liquid fund data in the actual own fund data, and adjusts the current user's wrong fund data list according to the historical fund data list corresponding to the investment preference; In the investment management system based on own funds analysis, after the funds data list is adjusted, the error information feedback module adjusts the funds data threshold interval in the funds data list analysis module according to the investment preferences of the current user in the user investment preference analysis module, and compares the funds data in the adjusted funds data list with the adjusted funds data threshold interval. If the actual own funds data after adjustment is not within the adjusted funds data threshold interval, the output is that the user intentionally filled in the wrong information, and the error information is fed back to the current user at this time. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is the overall module principle diagram of the present invention; Figure 2 It is a flow chart of the fund data list analysis module of the present invention; Figure 3 This is a flow chart of the user investment preference analysis module of the present invention.

[0014] The meaning of each number in the figure is: 100. Fund data list analysis module; 200. User investment preference analysis module; 300. Error information feedback module; 400. Investment project analysis module. DETAILED DESCRIPTION

[0015] The following will be combined with the accompanying drawings in 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.

[0016] The terms used in the exemplary embodiments shown in the drawings are not intended to limit the present invention. In the drawings, the same units / elements are given the same reference numerals.

[0017] Unless otherwise indicated, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0018] The following are some definitions of terms: Self-owned capital data refers to the capital data that an individual owns and can freely use for business operations, investments, and other activities; Liquidity data include bank deposit balances, cash holdings and other financial data; Non-current capital data include long-term investment, short-term investment and other capital data.

[0019] like Figure 1-3 As shown, the investment management system based on own funds analysis includes a fund data list analysis module 100, a user investment preference analysis module 200, an error information feedback module 300 and an investment project analysis module 400.

[0020] Before analyzing the own funds, the user needs to fill in the relevant data information according to his actual fund situation. However, in the specific process of filling in, some users with diversified investments may participate in many different types of investment activities, such as stocks, funds, foreign exchange, digital currencies, and real estate, equity and other assets on different platforms or regions. Due to the large number and variety of assets, it is easy to forget one or several investments and fill in the funds data incorrectly. Therefore, the present invention extracts the own funds data, liquid funds data and non-liquid funds data in the funds data list filled in by the user through the funds data list analysis module 100; The sum of the current funds data and the non-current funds data is the user's actual own funds data. If the actual own funds data is within the funds data threshold range, the output own funds data provided by the user is the user's actual own funds data; Otherwise, the output user's own funds data, current funds data and non-current funds data are filled in incorrectly; Specifically, the steps of the fund data list analysis module 100 extracting the own fund data, current fund data and non-current fund data from the fund data list provided by the user are as follows: First, mark the table names corresponding to own funds, current funds, and non-current funds; Then, the marked table names are compared one by one with the table names in the fund data list provided by the user by using the direct comparison method; After the comparison is completed, the fund data corresponding to the table names of own funds, current funds and non-current funds are retrieved, thereby extracting the own funds data, current funds data and non-current funds data in the fund data list.

[0021] Furthermore, the steps for the fund data list analysis module 100 to determine whether the actual own fund data is within the fund data threshold range are as follows: Receive own funds data in the funds data list , actual own funds data and funding data threshold range ; Calculate the actual own funds data range , ; like , then the own funds data in the output fund data list is the user's actual own funds data; like and When the current funds data and non-current funds data in the output funds data list are filled in incorrectly.

[0022] The present invention also fully considers that if the current user's liquid funds data and non-liquid funds data show a signal of filling in errors and fail to be adjusted in time, then when analyzing the own funds, the results obtained are bound to have a large deviation, which will have an adverse impact on the user's subsequent investment decisions. The present invention analyzes the user's investment preferences according to the proportion of liquid funds data and non-liquid funds data in the actual own funds data through the user investment preference analysis module 200; Sense the error signal of filling in the current fund data and the non-current fund data in the fund data list analysis module 100; Retrieving multiple sets of historical liquid fund data and historical illiquid fund data with the same investment preference as the current user, and calculating the similarity between the current and historical corresponding liquid fund data and illiquid fund data; Adjust the incorrect data based on the historical liquid funds data and historical non-liquid funds with the highest similarity.

[0023] Specifically, the steps of analyzing the user's investment preference in the user investment preference analysis module 200 are as follows: Receive liquidity data from historical user fund data respectively , Non-current Funds Data and actual own funds data ; ; ; in, and Liquidity data and illiquid funds data In actual own funds data The proportion of , it means that the user tends to keep most of the fund data in a state where it can be used at any time, pays more attention to the security and liquidity of the fund data, is more sensitive to risks, and is a conservative user; , it means that the user pays more attention to the accumulation and appreciation of long-term assets and is willing to lock the capital data in long-term and short-term investments, which means that the user is an aggressive user.

[0024] In order to facilitate the adjustment of the wrong information filled in the fund data list analysis module 100, the steps of calculating the similarity between the historical and current corresponding liquid fund data and non-liquid fund data in the user investment preference analysis module 200 are as follows: Sense the error signal of filling in the current fund data and the non-current fund data in the fund data list analysis module 100; Receive current user investment preferences, historical user investment preferences, historical liquid funds data, and historical illiquid funds data; Retrieve the current and current user's corresponding liquid fund data and non-liquid fund data; The similarity between multiple groups of historical liquid funds data, historical non-liquid funds data and the current user's liquid funds data and non-liquid funds data is calculated respectively. The calculation formula is as follows: ; in, Indicates the similarity between historical liquid funds data, historical non-liquid funds data and the current user's liquid funds data, non-liquid funds data, Indicates the number of users with the same investment preferences as the current user. The current user's liquidity data, It is the current user's non-liquidity data. For the Historical user liquidity data, For the Historical user illiquid funds data; like , then the output The historical liquid funds data and historical non-liquid funds data corresponding to the historical customers are most similar to the liquid funds data and non-liquid funds data corresponding to the current user.

[0025] Furthermore, in order to provide users with suitable investment projects, the steps of adjusting the wrong data filled in by the user investment preference analysis module 200 are as follows: Receive the fund data threshold interval in the fund data list analysis module 100 ; Receive current user liquidity data , Non-current Funds Data and historical user liquidity data , Non-current Funds Data ; The bank deposit balance in the historical liquidity data is , the bank deposit balance in the current user's liquidity data is ; like , , then the bank deposit balance of the current user's working capital data is output to be filled in incorrectly, and the bank deposit balance in the historical working capital data is adjusted to the bank deposit balance of the current user's working capital data; The bank deposit balance in the historical liquidity data is , the bank deposit balance in the current user's liquidity data is ; like , , then the bank deposit balance of the current user's non-liquidity data is output to be filled in incorrectly, and the bank deposit balance in the historical non-liquidity data is adjusted to the bank deposit balance of the current user's non-liquidity data; Because users with the same investment preferences will have similar trends and behavioral characteristics in their liquidity and illiquidity data when facing the same market environment, for example, conservative users usually tend to maintain a relatively stable capital structure, focusing on the security and liquidity of funds. When the market fluctuates, they will be more cautious in allocating liquidity to ensure that they can cope with possible sudden capital needs; Aggressive users are more keen on pursuing high-risk and high-return investment opportunities, and often allocate a large amount of funds to illiquid funds. For example, when the market is good, they may further increase their investment in illiquid assets such as stocks and emerging industries in order to seek rapid appreciation of assets. Therefore, users of the same type can adjust the incorrect data they filled in.

[0026] The present invention further considers that different users, for different types of users, for the purpose of testing the accuracy and reliability of the system, intentionally fill in wrong capital data, and attempt to observe whether the system can accurately identify data anomalies by providing false capital information, so as to determine whether the system is accurate in analyzing the own capital data. Therefore, the system adjusts the capital data threshold interval according to the user's investment preference through the error information feedback module 300, receives the adjusted liquid capital data and non-liquid capital data in the user's investment preference analysis module 200, and calculates again whether the adjusted capital data is within the capital data threshold interval through the capital data list analysis module 100; When the actual own fund data adjusted by the user investment preference analysis module 200 is output as the own fund data provided by the user, otherwise, it is determined that the fund data filled in by the output user is wrong, and the error information is fed back to the current user.

[0027] In order to improve the accuracy of the fund data list analysis module 100 in determining the error data, the steps of the error information feedback module 300 in adjusting the fund data threshold interval are as follows: Receive the fund data threshold interval in the fund data list analysis module 100 , receiving the current user investment preference analyzed in the user investment preference analysis module 200; Aggressive users tend to participate in various complex and high-risk investment activities, such as frequent stock trading, investing in equity of emerging industry enterprises, participating in high-leverage financial derivatives transactions, etc. The corresponding capital flows are relatively complex, involving multiple different investment channels and asset categories, and the value and trading conditions of these assets change rapidly. Therefore, when filling out the capital list, due to the complexity and dynamic nature of the assets, it is easy to miss some investment projects or related capital details; If the current user's investment preference is aggressive, the fund data threshold interval will be increased. for: ; The investment strategy of conservative users focuses on the security and stability of assets. They usually allocate most of their funds to simpler and more mature asset categories, such as bank time deposits, government bonds, large blue-chip stocks, etc. The transaction frequency of these assets is relatively low, and the investment channels and recording methods are relatively standardized, which is convenient for users to manage and record; If the current user's investment preference is a conservative user, the fund data threshold range is lowered for: .

[0028] The investment project analysis module 400 is used to provide suitable investment projects for the current user based on the current user's investment preferences and the investment preferences of historical users with a certain degree of similarity; Specifically, the steps of the investment project analysis module 400 providing a suitable investment project for the current user are as follows: Receive the similarity calculated in the user investment preference analysis module 200 ; Retrieving historical investment users corresponding to the similarity, and then labeling the historical investment users according to the similarity; like ,but The corresponding historical investment user is , The corresponding historical investment user is , and so on, all historical investment users are labeled ; And calculate the users corresponding to the top 10% of historical users, ,in Indicates the number of historical users; The investment preferences of the top ten percent of users are retrieved for recommendation to current investment users.

[0029] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the description in the output book are only preferred examples of the present invention and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An investment management system based on own funds analysis, characterized by: It includes a fund data list analysis module (100), a user investment preference analysis module (200), an error information feedback module (300) and an investment project analysis module (400); The fund data list analysis module (100) extracts the own fund data, current fund data and non-current fund data in the fund data list, and sets a fund data threshold interval; If the actual own fund data is within the fund data threshold range, the output user-provided own fund data is the user's actual own fund data; otherwise, the output fund data filling error signal; The user investment preference analysis module (200) senses a signal indicating an error in filling in the fund data, analyzes the user's investment preference, retrieves multiple groups of fund data with the same investment preference as the current user according to the user's investment preference, and adjusts the incorrectly filled in fund data according to the fund data with the highest similarity; The error information feedback module (300) adjusts the threshold interval of the capital data according to the user's investment preference, and determines again whether the adjusted capital data is within the threshold interval of the capital data. If it is, the adjusted capital data is output as the user's capital data; otherwise, it is determined that the capital data filled in by the user is wrong. The investment project analysis module (400) senses multiple groups of fund data with the same investment preference as the current user, selects the investment preferences corresponding to the top ten percent of users, and provides suitable investment projects for the current user.

2. The investment management system based on own funds analysis according to claim 1, characterized in that: The steps of extracting the own funds data, current funds data and non-current funds data from the funds data list by the funds data list analysis module (100) are as follows: Mark the table names corresponding to own funds, current funds and non-current funds, and use the direct comparison method to compare the marked table names with the table names in the fund data list one by one; After the comparison is completed, the fund data corresponding to the table names of own funds, current funds and non-current funds are retrieved.

3. The investment management system based on own funds analysis according to claim 2 is characterized in that: The steps of the fund data list analysis module (100) determining whether the actual own fund data is within the fund data threshold range are as follows: Receive own funds data in the funds data list , actual own funds data and funding data threshold range ; Calculate the actual own funds data range , ; like , then the own funds data in the output fund data list is the user's actual own funds data; like and When the current funds data and non-current funds data in the output funds data list are filled in incorrectly.

4. The investment management system based on own funds analysis according to claim 2, characterized in that: The steps of analyzing the user's investment preference in the user investment preference analysis module (200) are as follows: Receive liquidity data from historical user fund data respectively , Non-current Funds Data and actual own funds data ; ； ； in, Liquidity data In actual own funds data The proportion of Non-current funds data In actual own funds data The proportion of , it indicates that the user is a robust user; , it indicates that the user is an aggressive user.

5. The investment management system based on own funds analysis according to claim 4 is characterized in that: The steps of calculating the similarity between the historical and current corresponding liquid capital data and non-liquid capital data in the user investment preference analysis module (200) are as follows: Sense a signal of error in filling in the current capital data and the non-current capital data in the capital data list analysis module (100); Receive current user investment preferences, historical user investment preferences, historical liquid funds data, and historical illiquid funds data; Retrieve the current and current user's corresponding liquid fund data and non-liquid fund data; Calculate the similarity between multiple groups of historical liquid funds data, historical non-liquid funds data and the current user's liquid funds data, non-liquid funds data. The calculation formula is as follows: ； in, Indicates the similarity between historical liquid funds data, historical non-liquid funds data and the current user's liquid funds data, non-liquid funds data, Indicates the number of users with the same investment preferences as the current user. The current user's liquidity data, It is the current user's non-liquidity data. For the Historical user liquidity data, For the Historical user illiquid funds data; like , then determine The historical liquid funds data and historical non-liquid funds data corresponding to the historical customers are most similar to the liquid funds data and non-liquid funds data corresponding to the current user.

6. The investment management system based on own funds analysis according to claim 5, characterized in that: The steps of the user investment preference analysis module (200) for adjusting incorrectly filled capital data are as follows: Receive the fund data threshold interval in the fund data list analysis module (100) ; Receive current user liquidity data , Non-current Funds Data and historical user liquidity data , Non-current Funds Data ; The bank deposit balance in the historical liquidity data is , the bank deposit balance in the current user's liquidity data is ; like , , then the bank deposit balance of the current user's working capital data is output to be filled in incorrectly, and the bank deposit balance in the historical working capital data is adjusted to the bank deposit balance of the current user's working capital data; The bank deposit balance in the historical liquidity data is , the bank deposit balance in the current user's liquidity data is ; like , , then the bank deposit balance of the current user's non-liquidity data is outputted with errors, and the bank deposit balance in the historical non-liquidity data is adjusted to the bank deposit balance of the current user's non-liquidity data.

7. The investment management system based on own funds analysis according to claim 6 is characterized in that: The steps of adjusting the threshold interval of fund data by the error information feedback module (300) are as follows: Receive the fund data threshold interval in the fund data list analysis module (100) , receiving the current user investment preference analyzed in the user investment preference analysis module (200); If the current user's investment preference is aggressive, the fund data threshold interval will be increased. for: ; If the current user's investment preference is a conservative user, the fund data threshold range is lowered for: .

8. The investment management system based on own funds analysis according to claim 5, characterized in that: The steps of the investment project analysis module (400) providing a suitable investment project for the current user are as follows: Receiving the similarity calculated in the user investment preference analysis module (200) ; Retrieving historical investment users corresponding to the similarity, and then labeling the historical investment users according to the similarity; like ,but The corresponding historical investment user is , The corresponding historical investment user is , and so on, all historical investment users are labeled ; And calculate the users corresponding to the top 10% of historical users, ,in Indicates the number of historical users; The investment preferences of the top ten percent of users are retrieved for recommendation to current investment users.

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