An open-ended bond-type bull fund performance index ranking method and system

Abstract

The application discloses an open bond-type gold bull fund performance index ranking method and system, comprising the following steps: acquiring public information disclosure data of public funds, and constructing a basic database; according to a preset qualification condition, screening funds meeting the condition from the basic database to form a sample pool of participating funds; for each fund in the sample pool of participating funds, triggering a pre-calculation module, calculating a basic yield rate index corresponding to each trading day in an investigation period, and based on the net asset value disclosed in the fund regular report, interpolating and converting the scale weight of each trading day to obtain the basic index data set of the participating funds; according to the basic index data set of the participating funds, respectively calculating the risk-adjusted yield index and the contract compliance index of each participating fund in the investigation period; converting the risk-adjusted yield index and the contract compliance index into standard scores respectively, and performing weighted summation according to a preset weight to obtain the comprehensive score of each participating fund.

Description

Technical Field

[0001] This invention relates to the field of financial data processing technology, and in particular to a method and system for ranking the performance indicators of open-ended bond funds. Background Technology

[0002] Fund industry rankings help investors quickly filter out historically high-performing funds from a vast pool of options, improving decision-making efficiency. A consistently high ranking usually reflects strong stock selection, market timing, and risk control capabilities from fund managers and their research teams. Meanwhile, ranking changes can reflect shifts in market style, competitive distribution channels, and the success or failure of company strategies.

[0003] The ranking of my country's fund industry is an important indicator reflecting the competitive landscape of the industry. Its current situation is characterized by concentration among the top players and intensified competition. It has important reference value for investors' decision-making, but there are also problems such as data transparency, evaluation standards, and short-term behavior.

[0004] When faced with massive amounts of data such as net asset value, size, and government bond yield of thousands of funds over a long period (5 or 7 years), using traditional serial calculations or real-time join queries can lead to problems such as database I / O bottlenecks, memory overflows, or extremely long calculation times (high system response latency).

[0005] How to effectively process the aforementioned financial data and obtain a fair and effective ranking is a technical problem that needs to be solved. Summary of the Invention

[0006] In view of the problems existing in the prior art, the purpose of this invention is to provide a method for ranking the performance indicators of open-ended bond funds that can accurately and quickly obtain relevant rankings by effectively processing financial data. Another purpose of this invention is to provide a system for ranking the performance indicators of open-ended bond funds that implements the above method.

[0007] To achieve the above objectives, this invention provides a method for ranking the performance indicators of open-ended bond funds, comprising the following steps: Obtain publicly disclosed information data from public funds and construct a basic database that includes fund net asset value, benchmark index, and risk-free rate of return; Based on the preset eligibility criteria, funds that meet the criteria are selected from the basic database using a data filtering algorithm to form a sample pool of participating funds. For each fund in the sample pool of participating funds, the pre-calculation module is triggered to calculate the basic return rate indicator for each trading day during the observation period, and interpolation is performed based on the net asset value disclosed in the fund's periodic reports to generate the size weight for each trading day, thus obtaining the basic indicator dataset of the participating funds. Based on the basic indicator dataset of the participating funds, the risk-adjusted return indicator and contract compliance indicator of each participating fund during the observation period were calculated. The calculation process used size weights to weight the indicators. The risk-adjusted return indicator and the contract compliance indicator are converted into standard scores, and then weighted and summed according to preset weights to obtain the comprehensive score of each participating fund. The participating funds are then ranked and output based on the comprehensive scores.

[0008] Furthermore, the pre-set eligibility criteria include: Operating time condition: The operating time of the fund from its establishment to the end of the observation period shall not be less than the preset number of months threshold; Asset size criteria: Calculate the total average net asset value of similar funds during the observation period, sort them by average net asset value of individual funds from high to low and sum them up, and select funds whose cumulative size is within the preset percentage of the total; Fund manager tenure requirements: The current fund manager must have managed the fund for a cumulative period of no less than half of the total duration of the probationary period.

[0009] Furthermore, each data record in the basic indicator dataset of the participating funds is a multi-dimensional vector:

[0010] in, Indicates the fund code for the evaluation. This indicates one trading day during the observation period. This represents the rolling 1-year fund return. This represents the rolling 1-year benchmark yield. This represents the rolling one-year risk-free rate of return. This indicates the size weight of the participating fund on that trading day.

[0011] Furthermore, based on the net asset value disclosed in the fund's periodic reports, interpolation is performed to generate the size weight for each trading day. The calculation formula is: For trading days Obtain the comparable net asset size disclosed at the end of the most recent quarter before and after. and ,as well as Number of trading days between the most recent disclosed day and ; calculate scale of time conversion :

[0012] Calculate the total scale of the observation period :

[0013] Calculate the size weight for that trading day .

[0014] Furthermore, when constructing the basic database and pre-calculating basic indicators, for funds with multiple share classes, a unified data merging process is performed: For unit net asset value data, the system automatically extracts the fund's main share data for calculation.

[0015] Furthermore, when constructing the basic database and pre-calculating basic indicators, for funds with multiple share classes, a unified data merging process is performed: The system uses the aggregated data from the periodic reports after merging all fund share values ​​to calculate the net asset value and weighted average net asset value return rate of the fund.

[0016] Furthermore, the process of converting the indicators into standard scores and weighted summing specifically includes: using the z-score algorithm to standardize the risk-adjusted return indicator series and contract compliance indicator series of all participating funds respectively, eliminating the difference in dimensions to obtain standard scores.

[0017] Furthermore, the overall score is calculated according to a preset weighting formula with the risk-adjusted return indicator accounting for 80% and the contract compliance indicator accounting for 20%.

[0018] Furthermore, in the steps of calculating the risk-adjusted return index and the contract compliance index: since the calculation process of the evaluation index of each participating fund is independent of each other, the system calls multi-threaded or multi-process resources to allocate the funds in the sample pool of participating funds to different computing nodes for parallel processing, so as to improve the overall performance of the ranking calculation.

[0019] A performance ranking system for open-ended bond funds, the system being used to implement the aforementioned performance ranking method for open-ended bond funds, the system comprising a processor and a memory storing a computer program, wherein the processor, when executing the program, implements the following modules: Basic Data and Screening Module: Used to acquire publicly disclosed data to build a basic database, and to screen out a sample pool of participating funds based on operating time, asset size and fund manager tenure. Indicator pre-calculation module: For participating funds, it calculates the basic indicators, including fund return, benchmark return, and risk-free rate of return, for each trading day during the evaluation period, and generates daily size weights by interpolation based on the net asset value disclosed in adjacent periodic reports, and saves them to the basic database. Evaluation Calculation Module: Used to extract pre-calculated indicators and weights, and uses a parallel computing architecture to calculate the pseudo-Sotinho ratio and pseudo-Sotinho information ratio for each participating fund. The summary ranking module is used to convert the indicators output by the evaluation calculation module into standard scores, and then calculate the comprehensive score and output the ranking based on the preset weights.

[0020] The beneficial effects of this invention are as follows: 1. Pre-calculation and caching mechanism for basic indicators (improving data retrieval and calculation efficiency) Before performing complex risk-adjusted return calculations, this invention pre-calculates the basic indicators (such as the rolling 1-year fund return, the rolling 1-year benchmark return, and the risk-free rate of return) for each participating fund on each trading day during the evaluation period, and saves this data to the basic database. This preprocessing mechanism effectively avoids repeated retrieval and calculation of underlying data when executing highly complex evaluation models, significantly improving the overall computational performance of the system.

[0021] 2. Time-weighted interpolation algorithm for asset size (accurate mapping from low-frequency data to high-frequency data) In generating the daily weights required for calculation, this invention does not crudely use a single static data set, but instead designs an interpolation and conversion logic: for any trading day, this invention obtains the net asset value disclosed at the end of the most recent quarter before and after it, and performs cross-weighted calculations based on the actual number of trading days between that trading day and the disclosure dates before and after it. This data processing method can smoothly and dynamically map low-frequency quarterly asset data into high-frequency daily weight vectors, improving the accuracy of data calculation.

[0022] 3. Parallel processing architecture based on independent tasks (breaking through the bottleneck of computing power for massive data) In the most critical and time-consuming stages of calculating the "pseudo-Sotinho ratio" and "pseudo-Sotinho information ratio," the system identifies that the underlying indicator calculations for each participating fund (such as the weighted median and weighted lower standard deviation) are logically completely independent. Based on this characteristic, this invention employs a multi-threaded or multi-process parallel computing architecture to execute computational tasks simultaneously. This architecture-level design significantly accelerates overall performance and solves the computational power and time consumption issues when ranking massive amounts of similar funds across the entire market.

[0023] 4. Standardized fusion and cleaning of multi-source heterogeneous / multi-share data To address the common technical challenge of "one fund, multiple share classes" (leading to inconsistent data dimensions and definitions) in the entire fund market, this invention establishes an automated module for processing data with unified calculation standards during the data preparation stage: for high-frequency data such as unit net asset value, the system extracts the main share data; for low-frequency aggregated data such as asset size and profit margin, the system extracts the consolidated periodic report data. This structured data cleaning and fusion method ensures that the underlying data input into the evaluation model has high representativeness and cross-sample comparability. Attached Figure Description

[0024] Figure 1 A flowchart illustrating the overall ranking of performance indicators for open-ended bond funds that have achieved top performance. Figure 2 A flowchart for calculating the performance indicators and overall score of open-ended bond funds; Detailed Implementation

[0025] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0027] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0028] The following combination Figures 1-2 Specific embodiments of the present invention will be described in detail below. It should be understood that the specific embodiments described herein are for illustrative and explanatory purposes only and are not intended to limit the present invention.

[0029] This invention discloses a method for ranking the performance indicators of open-ended bond funds (Golden Bull Funds), comprising the following steps: Obtain publicly disclosed information data from public funds and construct a basic database that includes fund net asset value, benchmark index, and risk-free rate of return; Based on the preset eligibility criteria, funds that meet the criteria are selected from the basic database using a data filtering algorithm to form a sample pool of participating funds. For each fund in the sample pool of participating funds, the pre-calculation module is triggered to calculate the basic return rate indicator for each trading day during the observation period, and interpolation is performed based on the net asset value disclosed in the fund's periodic reports to generate the size weight for each trading day, thus obtaining the basic indicator dataset of the participating funds. Based on the basic indicator dataset of the participating funds, the risk-adjusted return indicator and contract compliance indicator of each participating fund during the observation period were calculated. The calculation process used size weights to weight the indicators. The risk-adjusted return indicator and the contract compliance indicator are converted into standard scores, and then weighted and summed according to preset weights to obtain the comprehensive score of each participating fund. The participating funds are then ranked and output based on the comprehensive scores.

[0030] 1.1 Evaluation and Calculation Tasks This invention uses the Golden Bull Award selection in the fund industry as a background and example to illustrate the detailed technical solution of this invention. The calculation task for the Golden Bull Fund Product Award selection is defined by the following seven-tuple: ProductAwardTask = (TaskName, FundType, RunType, EvalEndDate, EvalYears, Qualifications, ScoreModel). Wherein: TaskName: Product Award Selection Calculation Task Name FundType: The third-level classification to which the participating fund belongs (or second-level if none exists). RunType: The operating mode of the participating fund (open-ended / closed-ended) EvalEndDate: Deadline for evaluation (e.g., the deadline for the Golden Bull Award evaluation is 2024-12-31). EvalYears: The number of years for the observation period (five or seven years). Qualifications: Eligibility criteria for participation, expressed as a Boolean expression. ScoreModel: Scoring Model Each evaluation calculation task can be described as follows: Based on the sample pool of participating funds defined by the task (determined by FundType, RunType, and Qualifications), calculate the relevant evaluation indicators for each participating fund during the corresponding observation period (determined by EvalYears and EvalEndDate), further calculate the comprehensive score of each participating fund during the observation period according to the ScoreModel, and sort all participating funds in descending order of comprehensive score, which is the quantitative evaluation output of the task.

[0031] Based on the above definitions and the established award categories and classification system for Golden Bull Award funds, there are a total of 8 calculation tasks for the selection of open-ended bond-type Golden Bull fund products, as shown in Table 1 below: Table 1: Overview of Calculation Tasks for the Selection of Open-Ended Bond Funds (Golden Bull Funds)

[0032] For each calculation task in the table above, the subsequent calculation steps and processes need to be executed independently to obtain the quantitative evaluation ranking results for each task.

[0033] 1.2 Evaluation Index System The quantitative evaluation indicators for open-ended bond funds that achieve top performance are shown in Table 2 below: Table 2 Quantitative Evaluation Index System for Open-Ended Bond Funds (Golden Bull Funds)

[0034] When ranking similar funds, the most crucial calculation task is to calculate the two evaluation indicators in the table above for each fund that meets the eligibility criteria (hereinafter referred to as the participating fund) during the corresponding observation period, and then to calculate the comprehensive score of each participating fund based on their respective weights, and rank them accordingly.

[0035] 1.2.1 Indicators for Individual Funds remember Let F be the set of all such trading days for fund F during the observation period, arranged in chronological order: If a fund is purchased on the trading day preceding each specified date and held for h trading days before redemption, the redemption date must still be within the observation period. This is especially true when h is d, w, m, or y. These represent a set consisting of a trading day, a trading week, a trading month, and a trading year, respectively.

[0036] Performance: Absolute return and excess return (1) Sample of Fund F's return: for any given time period ,investor The return on fund F purchased on the previous trading day and held for h trading days is denoted as . A set arranged in chronological order is abbreviated as . ,Right now ; (2) Sample of Fund F's Risk-Free Return: For any given time period ,investor The annualized return of fund F purchased on the previous trading day and held for h trading days minus The yield of a 10-year Treasury bond with a maturity of h on the previous trading day is denoted as A set arranged in chronological order is abbreviated as . ,Right now The yields of government bonds of various maturities are all annualized, so the fund yields are also required to be annualized, and the geometric method is used for annualization. (3) Sample of excess returns of Fund F: for any given time period ,investor The return of buying fund F on the previous trading day and holding it for h trading days minus the investor's... The return on the benchmark fund F purchased on the previous trading day and held for h trading days is denoted as . A set arranged in chronological order is abbreviated as . ,Right now .

[0037] 1.2.2 Risk-Adjusted Performance Indicators (1) The total size and trading day weighting of Fund F during the observation period: On any trading day during the observation period , record fund On the trading day The net asset value disclosed at the end of the most recent quarter, after being converted using the conversion factor, yields the comparable net asset value (hereinafter referred to as "size"), which is denoted as follows: , ,time The number of trading days between the most recent disclosed trading volume and the last disclosed trading volume were respectively , If time It is precisely because of this large-scale announcement that... = , = like definition

[0038] This can be referred to as the total size of Fund F during the observation period. (Record again)

[0039] say For the return vector and The common weighted weights, where For set The number of elements.

[0040] (2) The pseudo-sorcinol ratio and pseudo-sorcinol information ratio are respectively:

[0041]

[0042] (M) represents the median. express The median of this dataset; This represents the lower standard deviation of the sample, where the "sample mean" used in calculating the standard deviation is the median. express The lower standard deviation of the samples in this dataset.

[0043] 1.2.3 Calculation method for summarizing scores of multiple scoring indicators under the same category Individual awards for fund products and fund company awards often have multiple scoring indicators. This award scheme uses a weighted summation method to aggregate these indicators into a single indicator, where the weights are predetermined. Because individual awards and company awards are selected within a single category, and categories are comparable, but the dimensions of each scoring indicator may not be identical, standardization is necessary before weighted summation. The specific method is as follows: 1) Establish an individual award or company award in the category of Selected from the middle, and have Each scoring indicator is set in category Members , The scores on these indicators are respectively , .

[0044] 2) For all members in the class, the first... A vector composed of indicators After standardization, it is denoted as .

[0045] 3) Record The weighted summation weight of each scoring indicator is: ;

[0046] 4) Then the members of the class Overall score for: ; Then according to The size of the award determines which members are eligible to be nominated.

[0047] 1.2.4 Calculation Scope of Indicators In fund evaluation, to ensure consistent calculation methods, funds with multiple share classes will be handled according to the following principles: 1) Except for the unit net value, all other indicators (such as fund size, weighted average net value return rate, etc.) use the consolidated data disclosed in the fund's periodic reports.

[0048] 2) The net asset value per unit uses data from the fund's main share.

[0049] The above principles are mainly based on the following considerations: 1) Consolidated data reflects the overall operation of the fund and is more representative and comparable.

[0050] 2) The information required to weight or combine the net asset value per unit of different shares is incomplete, and there are technical difficulties; the difference in net asset value per unit of different shares of the same fund is small, and the net asset value of the main share is representative, so the net asset value per unit of the main share is used for calculation.

[0051] 1.3 Overall Calculation Process The overall calculation process for the comprehensive ranking of open-ended bond fund performance indicators is as follows: Figure 1 As shown.

[0052] The overall data processing and calculation process consists of five steps: The first step is to prepare the basic data. Based on publicly disclosed information from public funds, a basic database for the Golden Bull Awards selection will be constructed. This database will store and record the basic data related to the entire Golden Bull Awards selection calculation process. In addition, based on the Golden Bull Awards fund classification system, all funds in the market will be classified, tagged with category labels, and any historical changes in fund classifications will be recorded.

[0053] The second step is the selection of participating funds. Based on the eligibility criteria for open-ended bond funds in the "Selection Scheme," funds meeting the eligibility criteria are selected from the Golden Bull Award's basic database to form the participating fund sample pool. Each subsequent calculation step is performed within this pool of participating funds.

[0054] The third step is to pre-calculate the basic indicators of the participating funds. To facilitate the verification of the calculation process, improve the overall calculation performance, and avoid repeatedly calculating some basic indicators (such as "the return rate of buying this fund on the previous trading day and holding it for one year") when calculating various evaluation indicators later, these indicators can be pre-calculated and saved to the Golden Bull Award selection database.

[0055] The fourth step is to calculate the performance evaluation indicators for participating funds. For each participating fund, calculate its various scoring indicators during the evaluation period (e.g., the evaluation period for the 22nd Golden Bull Award is from January 1, 2020 to December 31, 2024) as shown in Table 2.

[0056] The fifth step is to calculate and rank the comprehensive scores of the participating funds. For each participating fund, the relevant scoring indicators are weighted and summed according to the scoring model to obtain a comprehensive score. Then, the funds are ranked from highest to lowest based on their comprehensive scores.

[0057] The data processing flow, indicator calculation methods, or related algorithms involved in each of the above steps are described below.

[0058] I. Basic Data Preparation Based on publicly disclosed information from public funds, a foundational database for the Golden Bull Awards selection was constructed (technology selection: MySQL relational database). This database stores and records historical basic data related to the entire Golden Bull Awards selection calculation process, mainly including: basic information and changes of fund products, fund manager appointment and change information, daily net asset value data of funds, fund dividend or split data, 10-year Treasury bond yield data, daily benchmark index data, quarterly reports of funds (net asset value, asset allocation, etc.), and semi-annual or annual reports of funds (including ending net asset value, beginning net asset value, fund subscription proceeds, fund redemption proceeds, income distribution to holders, weighted average net asset value return rate, and profit for the period).

[0059] In practice, the basic database for the Golden Bull Awards can be built and maintained based on the Hengsheng Juyuan database, Wind database, or similar databases in the industry through ETL, data fusion, cross-validation, and incremental updates.

[0060] Based on the fund contracts' provisions regarding the fund's asset investment scope and proportions, and the equity and bond composition ratio of the performance benchmark, all funds in the market are classified (including liquidated funds). The classification information for each fund (including historical changes) is recorded in the Golden Bull Awards' basic database. If a fund's classification has changed historically due to changes in its investment scope or performance benchmark, the database must record the classification information before and after the change (including the fund's category label, effective date, and expiration date at each stage before and after the change).

[0061] II. Selection of Participating Funds Based on the Golden Bull Award selection database, funds that meet the eligibility criteria for participating in the Golden Bull Award for open-ended bond funds are selected to form a sample pool of participating funds (each subsequent calculation step is carried out in this sample pool of funds).

[0062] Funds eligible to participate in the selection of open-ended bond fund products for the Golden Bull Award must meet the following eligibility criteria: (1) Operation time requirement: For funds participating in the five-year (or seven-year) product award, the operation time from the product's establishment to the end of the evaluation period shall not be less than 60 months (or 84 months).

[0063] (2) Asset size requirements: For each type of fund, the average net asset value during the observation period is ranked from high to low. The average net asset value after ranking is added up in sequence, and the products with the cumulative total size accounting for the top 90% of the total size of similar products are selected.

[0064] (3) Fund manager tenure requirement: The current fund manager should have managed the product for no less than half of the probationary period.

[0065] (4) The following is the sample selection process for participating funds:

[0066] Taking the "Open-ended Bond Fund - Pure Bond Fund - 5Y" task of the "Golden Bull Award for Five-Year Open-ended Bond Funds" in Table 1 as an example, the input parameters when using the above screening algorithm are: FundType = "Pure Bond Fund", RunType = "Open-ended", EvalEndDate = "2024-12-31", EvalYears = 5. After executing this screening algorithm, the resulting fund sample set is the sample pool of participating funds for the "Open-ended Bond Fund - Pure Bond Fund - 5Y" evaluation task. Subsequent processes will only need to perform indicator calculations and scoring rankings for each participating fund in this sample pool.

[0067] III. Preliminary Calculation of Basic Indicators for Participating Funds For each participating fund, its relevant basic indicators for each trading day during the evaluation period are calculated and saved to the Golden Bull Award evaluation database. This avoids redundant calculations during subsequent indicator calculations, effectively improving overall computational performance. These basic indicators for each participating fund on each trading day collectively form a six-tuple, forming the overall basic indicator dataset for the participating funds.

[0068] Where: F represents the participating fund (usually identified by the fund code). This indicates one trading day during the observation period. This represents the return on an investor who buys F on the previous trading day of t and holds it for one year (hereinafter referred to as "rolling 1-year fund return"). This represents the return on an investor who bought the benchmark F on the previous trading day of t and held it for one year (hereinafter referred to as the "rolling 1-year benchmark return"). This represents the risk-free rate of return for an investor who buys a 10-year Treasury bond on the previous trading day of t and holds it for one year (hereinafter referred to as the "rolling 1-year risk-free rate"). This indicates the size weight (comparable net asset value after conversion) of the participating fund F on that trading day.

[0069] IV. Calculation of Performance Evaluation Indicators for Participating Funds Based on the basic indicator dataset D of the participating funds obtained in the previous steps, the specific algorithms and calculation processes of each performance evaluation indicator in "Table 2. Quantitative Evaluation Indicator System for Open-ended Bond Golden Bull Funds" are explained below. Figure 2 The overall calculation process from calculating each evaluation index to obtaining the final comprehensive score is given (since the various indicators are independent of each other, they can be calculated in parallel to speed up the overall performance).

[0070] The specific algorithms and calculation processes for each performance evaluation indicator are described below.

[0071] 4.1 Calculation of Risk-Adjusted Return Indicator The risk-adjusted return of the participating funds during the evaluation period is measured using the "prototype Sortino ratio," calculated as follows:

[0072] in, This represents the dataset of the risk-free rate of return for the participating fund F, where each data point represents the risk-free rate of return of the participating fund F in ascending order of trading days during the observation period; This represents the weighted median of the ultra-risk-free rate dataset for the participating fund F; This represents the weighted lower standard deviation of the ultra-risk-free rate dataset for the participating fund F.

[0073] The calculation process for the risk-adjusted return of participating fund F during the evaluation period is as follows:

[0074] The above process is repeated for each participating fund to obtain its pro forma Sortino ratio during the observation period, which is the risk-adjusted return indicator value of that fund during the observation period. Since the calculation of the pro forma Sortino ratio of each participating fund is independent of each other, parallel computing methods can be used to speed up the overall performance (for example, by using multi-threading or multi-processing to execute the above process in parallel).

[0075] 4.2 Calculation of Contract Compliance Indicators The contract compliance rate of participating funds during the evaluation period is measured using the "prototype Sortino information ratio," calculated using the following formula:

[0076] in, This represents the excess return data of the participating fund F relative to its performance benchmark, where each data point represents the excess return of the participating fund F in ascending order of trading days during the observation period; This represents the weighted median of the excess return dataset for the participating fund F; This represents the weighted lower standard deviation of the excess return dataset of the participating fund F.

[0077] The calculation process for the risk-adjusted relative return of participating fund F during the evaluation period is as follows:

[0078] Similarly, the above process is repeated for each participating fund to obtain its proposed Sortino Information Ratio (PIR) during the observation period, which is the indicator of the fund's contract compliance during the observation period. Since the PIRs of each participating fund are independent of each other, parallel computing can be used to speed up the overall performance (e.g., by using multi-threading or multi-processing to execute the above process in parallel).

[0079] V. Calculation and Ranking of the Overall Score of Participating Funds After the evaluation indicators for all participating funds were calculated, each indicator was converted into a standard score (based on zscore). Then, the scores were weighted and summed according to the weights of each indicator in "Table 2: Quantitative Evaluation Indicator System for Open-Ended Bond Funds" to obtain the comprehensive score for each participating fund. Overall Score = Standard Score of Risk-Adjusted Return Indicator + Contract Compliance Indicator Standard Score .

[0080] The final ranking of participating funds is obtained by sorting them from highest to lowest based on their overall scores.

[0081] VI. Simultaneously, this invention also provides a performance indicator ranking system for open-ended bond funds, the system being used to implement the aforementioned performance indicator ranking method for open-ended bond funds. The system includes a processor and a memory storing a computer program. When the processor executes the program, it implements the following modules: Basic Data and Screening Module: Used to acquire publicly disclosed data to build a basic database, and to screen out a sample pool of participating funds based on operating time, asset size and fund manager tenure. Indicator pre-calculation module: For participating funds, it calculates the basic indicators, including fund return, benchmark return, and risk-free rate of return, for each trading day during the evaluation period, and generates daily size weights by interpolation based on the net asset value disclosed in adjacent periodic reports, and saves them to the basic database. Evaluation Calculation Module: Used to extract pre-calculated indicators and weights, and uses a parallel computing architecture to calculate the pseudo-Sotinho ratio and pseudo-Sotinho information ratio for each participating fund. The summary ranking module is used to convert the indicators output by the evaluation calculation module into standard scores, and then calculate the comprehensive score and output the ranking based on the preset weights.

[0082] Any process or method described in the flowcharts of this invention or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, which can be implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device. The computer-readable medium can be any medium containing a program for storage, communication, propagation, or transmission for use by an execution system, apparatus, or device, including read-only memory, magnetic disks, or optical disks.

[0083] In the description of this specification, references to terms such as "embodiment," "example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, those skilled in the art can combine or combine the different embodiments or examples described in this specification and the features therein without causing contradiction.

[0084] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Therefore, any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention should fall within the protection scope of the present invention.

Claims

1. A method for ranking the performance indicators of open-ended bond funds, characterized in that, Includes the following steps: Obtain publicly disclosed information data from public funds and construct a basic database that includes fund net asset value, benchmark index, and risk-free rate of return; Based on the preset eligibility criteria, funds that meet the criteria are selected from the basic database using a data filtering algorithm to form a sample pool of participating funds. For each fund in the sample pool of participating funds, the pre-calculation module is triggered to calculate the basic return rate indicator for each trading day during the observation period, and interpolation is performed based on the net asset value disclosed in the fund's periodic reports to generate the size weight for each trading day, thus obtaining the basic indicator dataset of the participating funds. Based on the basic indicator dataset of the participating funds, the risk-adjusted return indicator and contract compliance indicator of each participating fund during the observation period were calculated. The calculation process used size weights to weight the indicators. The risk-adjusted return indicator and the contract compliance indicator are converted into standard scores, and then weighted and summed according to preset weights to obtain the comprehensive score of each participating fund. The participating funds are then ranked and output based on the comprehensive scores.

2. The method according to claim 1, characterized in that, The pre-set eligibility criteria include: Operating time condition: The operating time of the fund from its establishment to the end of the observation period shall not be less than the preset number of months threshold; Asset size criteria: Calculate the total average net asset value of similar funds during the observation period, sort them by average net asset value of individual funds from high to low and sum them up, and select funds whose cumulative size is within the preset percentage of the total; Fund manager tenure requirements: The current fund manager must have managed the fund for a cumulative period of no less than half of the total duration of the probationary period.

3. The method according to claim 1, characterized in that, Each data record in the basic indicator dataset of the participating funds is a multi-dimensional vector: in, Indicates the fund code being evaluated. This indicates one trading day during the observation period. This represents the rolling 1-year fund return. This represents the rolling 1-year benchmark yield. This represents the rolling one-year risk-free rate of return. This indicates the size weight of the participating fund on that trading day.

4. The method according to claim 3, characterized in that, The size weight for each trading day is generated by interpolating and converting the net asset value disclosed in the fund's periodic reports. The calculation formula is: For trading days Obtain the comparable net asset size disclosed at the end of the most recent quarter before and after. and ,as well as Number of trading days between the most recent disclosed day and ; calculate scale of time conversion : Calculate the total scale of the observation period : Calculate the size weight for that trading day .

5. The method according to claim 1, characterized in that, When constructing the basic database and pre-calculating basic indicators, for funds with multiple share classes, a unified data merging process is performed: For unit net asset value data, the system automatically extracts the fund's main share data for calculation.

6. The method according to claim 1, characterized in that, When constructing the basic database and pre-calculating basic indicators, for funds with multiple share classes, a unified data merging process is performed: The system uses the aggregated data from the periodic reports after merging all fund share values ​​to calculate the net asset value and weighted average net asset value return rate of the fund.

7. The method according to claim 1, characterized in that, The process of converting indicators into standard scores and then weighting and summing them specifically includes: using the z-score algorithm to standardize the risk-adjusted return indicator series and contract compliance indicator series of all participating funds, respectively, to eliminate dimensional differences and obtain standard scores.

8. The method according to claim 7, characterized in that, The overall score is calculated using a pre-defined weighting formula, with the risk-adjusted return indicator accounting for 80% and the contract compliance indicator accounting for 20%.

9. The method according to claim 1, characterized in that, In the steps of calculating the risk-adjusted return index and contract compliance index: since the calculation process of the evaluation index of each participating fund is independent of each other, the system calls multi-threaded or multi-process resources to allocate the funds in the sample pool of participating funds to different computing nodes for parallel processing, so as to improve the overall ranking calculation performance.

10. A performance ranking system for open-ended bond funds, characterized in that, The system is used to implement the method as described in any one of claims 1 to 9, the system comprising a processor and a memory storing a computer program, wherein the processor, when executing the program, implements the following modules: Basic Data and Screening Module: Used to acquire publicly disclosed data to build a basic database, and to screen out a sample pool of participating funds based on operating time, asset size and fund manager tenure. Indicator pre-calculation module: For participating funds, it calculates the basic indicators, including fund return, benchmark return, and risk-free rate of return, for each trading day during the evaluation period, and generates daily size weights by interpolation based on the net asset value disclosed in adjacent periodic reports, and saves them to the basic database. Evaluation Calculation Module: Used to extract pre-calculated indicators and weights, and uses a parallel computing architecture to calculate the pseudo-Sotinho ratio and pseudo-Sotinho information ratio for each participating fund. The summary ranking module is used to convert the indicators output by the evaluation calculation module into standard scores, and then calculate the comprehensive score and output the ranking based on the preset weights.

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