WO2020037955A1

WO2020037955A1 - Index tracking error analysis method and apparatus, storage medium and computer device

Info

Publication number: WO2020037955A1
Application number: PCT/CN2019/074031
Authority: WO
Inventors: 黄逸湄; 王志博
Original assignee: 平安科技（深圳）有限公司
Priority date: 2018-08-22
Filing date: 2019-01-30
Publication date: 2020-02-27
Also published as: CN109409631A

Abstract

An index tracking error analysis method and apparatus, a storage medium and a computer device, relating to the technical field of information processing and capable of improving efficiency and accuracy of index tracking error analysis of an index fund. The method comprises: acquiring information data corresponding to an index fund (101); according to the acquired information data, determining index data of the index fund (102); analyzing the index data of the index fund to acquire return error cause information and risk error cause information of the index fund (103); and according to the return error cause information and risk error cause information of the index fund, determining an analysis result of an index tracking error of the index fund (104). The present application is suitable for index tracking error analysis of an index fund.

Description

Index tracking error analysis method and device, storage medium, computer equipment

This application claims priority from the Chinese patent application filed on August 22, 2018 with the Chinese Patent Office, application number 2018109631638, and application name "Index Tracking Error Analysis Method and Device, Storage Medium, Computer Equipment", all of which passed Citations are incorporated in the application.

Technical field

The present application relates to the field of information processing technology, and in particular, to an index tracking error analysis method and device, a storage medium, and a computer device.

Background technique

Investment performance evaluation can be divided into three parts, from the most basic use of quantitative indicators to describe the performance of portfolio performance to the deep-level portfolio excess income decomposition of the performance attribution, and finally form a mature performance evaluation, the excess return of the portfolio or fund Evaluation of sustainability.

At present, the index tracking error analysis of index funds requires manual calculation and analysis. Specifically, it needs to first obtain data sources from financial data and analysis tool service providers, then obtain basic data from the valuation system, import them into Excel spreadsheet files, and calculate. The calculation formula involves a large number of summing, rooting, matrix algorithms, etc., and then find out which sources of tracking error are based on the calculation results.

However, due to the tedious calculation operation steps, the efficiency of the index tracking error analysis will be affected, and the manual calculation analysis will inevitably have large errors, which will affect the accuracy of the index tracking error analysis.

Summary of the Invention

In view of this, this application provides an index tracking error analysis method and device, storage medium, and computer equipment. The main purpose is to solve the current index tracking error analysis for index funds, which requires manual calculation and analysis. Because of this calculation operation, The tedious steps will affect the efficiency of the index tracking error analysis, and there will inevitably be large errors in the manual calculation and analysis, which will affect the accuracy of the index tracking error analysis.

According to an aspect of the present application, an index tracking error analysis method is provided, and the method includes:

Obtaining information and data corresponding to index funds;

Determining the index data of the index fund according to the information data, wherein the index data includes an α coefficient index, a β coefficient index, a maximum retracement index, an annualized return index, and an accumulated return rate of the index fund Indicators, value-at-risk (Vaule, Riks, VAR) parameter indicators;

Analyzing, through the index data, the cause of return error and cause of risk error of the index fund;

An index tracking error analysis result of the index fund is determined according to the return error cause information and the risk error cause information.

According to another aspect of the present application, an index tracking error analysis device is provided. The device includes:

An obtaining unit for obtaining information data corresponding to the index fund;

A determining unit, configured to determine the index data of the index fund according to the information data obtained by the obtaining unit, wherein the index data includes an alpha coefficient index, a beta coefficient index, and a maximum retracement index of the index fund , Annualized return index, cumulative return index, VAR parameter index;

An analysis unit, configured to analyze, through the index data determined by the determination unit, the cause information of the return error and the cause of the risk error of the index fund;

The determining unit is further configured to determine an index tracking error analysis result of the index fund according to the return error cause information and the risk error cause information analyzed by the analysis unit.

According to yet another aspect of the present application, a non-volatile readable storage medium is provided, on which computer-readable instructions are stored, and the computer-readable instructions implement the foregoing index tracking error analysis method when executed by a processor.

According to yet another aspect of the present application, a computer device is provided, including a non-volatile readable storage medium, a processor, and computer-readable instructions stored on the storage medium and executable on the processor. The processor executes The computer-readable instructions implement the index tracking error analysis method described above.

By means of the above technical solution, an index tracking error analysis method and device, storage medium, and computer equipment provided by the present application are compared with the current method of implementing index tracking error analysis for index funds by manual and tedious calculations. According to the information data corresponding to the index fund, determine the alpha coefficient index, beta coefficient index, maximum retracement index, annualized return index, cumulative return index, VAR parameter index of the index fund, and then use these index data to analyze the index type The fund's return error cause information and risk error cause information can be used to obtain the index tracking error analysis result of the index fund, so that what can affect the index tracking error can be analyzed in real time, which improves the accuracy of the index tracking error analysis. Manual calculation also improves a certain analysis efficiency, helping to achieve real-time intra-day adjustment.

The above description is only an overview of the technical solution of this application. In order to understand the technical means of this application more clearly, it can be implemented in accordance with the content of the description, and in order to make the above and other purposes, features, and advantages of this application more obvious and understandable. The specific implementations of this application are listed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described here are used to provide a further understanding of the present application and constitute a part of the present application. The schematic embodiments of the present application and the description thereof are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

FIG. 1 is a schematic flowchart of an index tracking error analysis method according to an embodiment of the present application;

FIG. 2 is a schematic flowchart of another index tracking error analysis method according to an embodiment of the present application; FIG.

3 is a schematic structural diagram of an exponential tracking error analysis device according to an embodiment of the present application;

FIG. 4 is a schematic structural diagram of another index tracking error analysis device according to an embodiment of the present application.

detailed description

Hereinafter, the present application will be described in detail with reference to the drawings and embodiments. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

In order to solve the problem of index tracking error analysis of index funds that currently rely on manual and tedious calculations, which will affect the efficiency and accuracy of index tracking error analysis, an index tracking error analysis method is provided in this embodiment, which can improve the index The efficiency and accuracy of tracking error analysis is shown in Figure 1. The method includes:

101. Obtain information data corresponding to an index fund.

Among them, the information data may include data on the positions of each share, data on the market value of each share, data on fund application and redemption, data on the cost of funds, and data on the changes in fund assets. Among them, the data on the position of each share includes the position of each stock under the fund; The market value change data of each share includes the market value change of each stock under the fund; the fund application and redemption status data includes the purchase and sale of each stock under the fund; the fund cost situation includes the risk margin required for the fund to buy and sell stocks; the fund Data on asset changes include the frozen funds and liquidity of the fund.

The execution subject of this embodiment may be an index tracking error analysis device or device, which is used for index tracking error analysis of an index fund. The device or equipment uses the information of the index fund to analyze, analyze the reasons for the return error of the index fund and the cause of the risk error of the fund, and then analyze in real time what factors affect the index tracking error, so as to achieve timely and corresponding adjustment in the intraday. . For details, refer to the processes shown in steps 102 to 104.

102. Determine the index data of the index fund according to the obtained information data.

Among them, the index data includes alpha coefficient index, beta coefficient index, maximum retracement index, annualized return index, cumulative return index, and VAR parameter index of index funds.

The α coefficient refers to the difference between the actual risk return and the average expected risk return, and reflects the return that the fund receives due to changes in the overall market.

The beta coefficient, called Beta Coefficient, is a risk index used to measure the price fluctuations of individual stocks relative to the entire stock market. The higher β, the greater the volatility of the stock relative to the performance evaluation benchmark. β is greater than 1, the volatility of the stock is greater than the volatility of the performance evaluation benchmark. vice versa. If β is negative, it shows that the direction of change is opposite to that of the broader market; when the broad market is up, it falls, and when the broad market is down, it rises.

Maximum retracement refers to the largest range from the peak to the bottom of the index fund's net worth curve. This indicator tests the fund manager's ability to grasp risks and trends; retracements are proportional to risk. The greater the retracement, the greater the risk and the retracement. The smaller the risk is.

The annualized rate of return refers to the rate of return of the investment period of the index fund for one year; the cumulative rate of return refers to the total rate of return from the establishment of the index fund to the current time.

The VAR parameter refers to the maximum possible loss of an index fund under normal market fluctuations. More precisely, it refers to the maximum possible loss of the value of index funds in a certain period in the future at a certain level of probability (confidence).

103. Analyze the index data of the index funds to obtain the information on the reasons for the return error and the reasons for the risks of the index funds.

Among them, the reason for the return error may include the reasons for the return error of the index fund; the information for the risk error may include the reasons for the risk error of the index fund.

In this embodiment, the two main factors that cause the tracking error of the index fund index are the return error and the risk error, respectively. The return error refers to the error between the return of the index fund's net value and the target return of the intraday index; and the risk error refers to the index fund's resistance to the wind

The error between the actual ability of the risk and the target ability value in the intraday. Among them, the target income and target ability value will be obtained by a third party at the close and given in advance.

Using the six indicator data in step 102, analyze what are the reasons for the return error of the index fund and what are the reasons for the risk error, and then comprehensively determine what factors affect the index tracking error.

104. Determine the analysis result of the index tracking error of the index fund based on the information on the cause of the return error and the risk error of the index fund.

Among them, the index tracking error refers to the deviation between the real-time index of the index fund and the target index. The target index is an authoritative index issued by a stock index company and corresponding to the index product of the index fund.

For this embodiment, after obtaining the return error reason information and risk error cause information of the index fund, you can analyze from these reasons the most important reasons (that is, the factors that cause the largest degree of error deviation) and the relatively minor reasons. What are the results? The analysis results are displayed in the form of tables, graphs, etc. according to the order of severity. It is convenient for users to intuitively understand what causes the index tracking error of index funds, which is convenient for timely adjustment and processing to ensure index type. The fund's index tracks the index as completely as possible.

By applying the technical solution of this embodiment, the index error of index funds can be analyzed using the α coefficient index, β coefficient index, maximum retracement index, annualized return index, cumulative return index, and VAR parameter index. Cause information and risk error cause information, that is, using the latest position data of each stock, market value data of each stock change, fund application and redemption, fund expenses, and changes in fund assets, etc., analyze in real time what factors affect the index tracking error Compared with the current method of relying on manual and tedious calculations to implement the index tracking error analysis of index funds, it can improve the accuracy of index tracking error analysis, and because it does not require manual calculations, it also improves certain analysis efficiency and helps to achieve Real-time adjustment.

Further, as a refinement and extension of the specific implementation of the above embodiment, in order to completely explain the specific implementation process of this embodiment, another method for analyzing the index tracking error is provided. As shown in FIG. 2, the method includes:

201. Obtain information data corresponding to an index fund.

In this embodiment, the information data of each stock under the index fund can be obtained, and further analysis is performed on these information data to realize the index tracking error analysis of the index fund, and then the investment performance attribution evaluation can be realized.

202. Determine the alpha coefficient index, beta coefficient index, maximum retracement index, annualized return index, cumulative return index, and VAR parameter index of the index fund according to the obtained information data.

Among them, the determination process of the β coefficient index may specifically include: calculating the overall market return rate of the index fund x according to the closing number of the latest period of the index corresponding to the index fund and the closing number of the previous period, and according to the index fund The closing price of the latest period of the next stock and the closing price of the previous period are used to calculate the yield y of each stock under the index fund; then use the formula COV (x, y) / VAR (x) to calculate the index type The β coefficient of each stock under the influence of the capital structure of the fund, and the use of the formula COV (x, y) / VAR (x) / (1+ (1-T) * D / E) to calculate the elimination of each stock under the index fund The β coefficient of the influence of capital structure, where T is the income tax rate of the company corresponding to the stock; D is the market value of the company's debt; E is the market value of the company's equity.

In the above formula, COV () stands for covariance function and VAR () stands for variance function. For example, the index fund that currently requires index tracking error analysis corresponds to the CSI 500 Index, and its β coefficient is calculated as follows: the overall market rate of return a = (the closing number of the latest period of the CSI 500 Index-CSI 500 Index Previous Closings at the end of the period) / Closings at the end of the previous period of the CSI 500 Index;

The return rate of stock i under the index fund b = (the closing price of the latest period of stock i-the closing price of the last period of stock i) / the closing price of the last period of stock i; use the formula β1 = COV (a , B) / VAR (a) Calculate the β coefficient of each stock affected by the capital structure; use the formula β2 = β1 / (1+ (1-T) * D / E) to calculate the β coefficient of each stock to eliminate the effect of capital structure , T is the income tax rate of the company corresponding to the stock; D is the market value of the company's debt corresponding to the stock; E is the market value of the company's equity corresponding to the stock.

The determination process of the α coefficient index may specifically include: calculating the product of COV (x, y) / VAR (x) and the profit value of the investment fund of the index fund for a predetermined period of time, and subtracting the absolute return of the index fund This product gives the alpha coefficient of the index fund.

Among them, the predetermined amount of funds can be the cash used by the user to invest in the index fund, and the preset time can take 1, 2 years, etc .; the absolute return of the index fund is the above-mentioned profit value minus the predetermined amount of funds corresponding to the preset time. The difference between investment returns. For example, the profit value of investing in the fund for a period of one year based on a fixed amount of funds, minus the regular return of the fixed amount of funds in a bank for a period of one year, and the difference obtained as the absolute return of the index fund.

The process of determining the annualized rate of return index may specifically include: dividing the internal investment return of the index fund by the principal, then dividing by the number of investment days, then multiplying by the total number of days in a year, and then multiplying by 100% to obtain the year of the index fund Profitability.

For example, the annualized return rate of an index fund = [(internal investment return / principal) / number of investment days] * 365 x 100%, annualized return = principal x annualized return rate, actual return = principal x annualized rate Yield × investment days / 365.

The process of determining the VAR parameter index may specifically include: using the formula M (ΔMΔt≤VaR) = N to calculate the VAR parameter of the index fund, where M is the probability that the asset value loss of the index fund is less than the preset upper loss limit, ΔM VaR is the value loss of the index fund during a certain holding period Δt, VaR is the value at risk at a predefined confidence level N.

By using the above-mentioned methods, each index data of the index fund can be accurately determined.

203. Based on the six index data of the index fund, analyze the cause information of the return error and the cause of the risk error of the index fund.

Wherein, the step of analyzing the cause information of the return error of the index fund may specifically include: separately calculating the first deviation error between each indicator in the indicator data and the respective preset target value; and then multiplying the first deviation error corresponding to each indicator by Take the corresponding predetermined weights and add them to get the sum; then divide the first deviation error of each indicator by the sum to get the first deviation error proportion of each indicator; then choose the first deviation error proportion The index whose ratio is greater than the preset ratio threshold and / or whose first deviation error is greater than the first preset deviation threshold is used as the first index to be analyzed; finally, the covariance matrix is used to calculate the first index to be analyzed and divided by each index. Correlation between indicators other than the first to-be-analyzed indicator; in order to determine the first to-be-analyzed indicator and an indicator with a strong correlation with the first-to-be-analyzed indicator as the first to affect the return error of the index fund The main error factor.

The preset target value, the predetermined weight, the preset ratio threshold, and the first preset deviation threshold can all be set in advance according to actual business requirements, and can be specifically set by referring to the index standard corresponding to the target index issued by the stock index company. Use the data of each indicator to calculate the covariance matrix. The horizontal and vertical in the matrix correspond to each indicator. In addition to the values on the diagonal in the matrix, the rest of the values in the matrix represent the relationship between the two different indicators, such as the horizontal and Vertically according to the α coefficient index, β coefficient index, maximum retracement index, annualized return index, cumulative return index, and value-at-risk parameter index, then the values in the first row and the second column of the covariance matrix correspond to α The value of the correlation between the coefficient index and the β-coefficient index; the values in the first row and the sixth column correspond to the value of the correlation between the α-coefficient index and the value-at-risk parameter index. The two indicators whose association relationship value is greater than a certain threshold value are determined to have a strong association relationship. A strong relationship indicates that the two indicators have a strong relationship. If one of the indicators changes, the other indicator with a strong relationship will also be affected and changed.

For example, calculate the deviation errors between the 6 indicators and their respective preset target values, weight the sum of these deviation errors, analyze the proportion of a single deviation error, select the indicator whose error proportion is greater than a certain threshold, or select the deviation error greater than a certain threshold The threshold index is used as the index to be analyzed, that is, the main factor that affects the return error. The covariance matrix is further used to calculate the correlation between these indicators to find the index that has a strong correlation with the main factor, because some main factors may It will be affected by other indicators, causing the deviation to be too large, so it needs to be taken together as the main error factor that affects the return error. The subsequent analysis of which combination has the greatest impact on the return error, and then adjust the combination to maximize the effect.

The step of analyzing the risk error cause information of the index fund may specifically include: using the normal distribution algorithm to calculate the expected deviation error of each indicator according to the second deviation error of each indicator; selecting the second deviation error greater than the corresponding expected value of the deviation error And / or an index whose second deviation error is greater than a second predetermined deviation error threshold is used as a second indicator to be analyzed, where the second predetermined deviation threshold can be specifically set according to the anti-risk factor of the index fund; the covariance matrix is used to calculate the first Correlation between the second to-be-analyzed index and other indicators except the second to-be-analyzed index; determine the second to-be-analyzed index and the index with a strong correlation with the second to-be-analyzed index as the impact index Risk factor is the second major error factor of fund.

For example, according to the historical deviation errors of the 6 indicators over the same period and the current deviation errors, use the normal distribution algorithm to calculate the expected deviation errors of each indicator, and then select the deviation errors that are greater than the corresponding deviation error expected values, and / or the deviation errors An index greater than a certain threshold is used as the index to be analyzed, that is, the main factor that affects the risk error. The covariance matrix is further used to calculate the correlation between these indicators to find indicators that have a strong correlation with the main factors, because some are The main factors may be affected by other indicators, causing the deviation to be too large, so they need to be taken together as the main error factors that affect the risk error. The subsequent detailed analysis of which combination has the greatest effect on the risk error, and then adjust the combination to maximize the effect .

For this embodiment, through the above two methods, not only the deviation effect of a single indicator is considered, but also the comprehensive deviation effect of the combination between the indicators is considered, which is more in line with the actual situation of the business, and the reason for the return error of the index fund can be accurately analyzed. Information and risk error cause information.

204. Determine the same factor existing in the first main error factor and the second main error factor as the main factor that affects the index tracking error of the index fund.

For the present embodiment, if the same index exists in the main error factor of the return error of the index fund and the main error factor of the risk error, then it can be determined that this index not only mainly affects the return error of the index fund, but also mainly affects the index type. Funds cause risk errors, and this indicator is determined to be the main factor affecting the index tracking error of index funds.

For example, if the α coefficient is both the main error factor of the return error of index funds and the main error factor of the risk error of index funds, then the α coefficient is the main factor affecting the index tracking error of index funds, that is, the deviation of the α coefficient is The main reason for index tracking errors in index funds.

205. Determine the difference factor between the first major error factor and the second major error factor as a minor factor that affects the index tracking error of the index fund.

For this embodiment, different indexes of the main error factor of the index fund's return error and the risk error's main error factor can be determined as the secondary factors that can affect the index tracking error of the index fund. Although these indexes have no major The degree of influence of the factor is large, but there is a certain error in the index tracking of index funds.

Further, in order to obtain the best adjustment effect, as a preferred method, the method in this embodiment may further include: querying an adjustment strategy corresponding to an index corresponding to the main factor from a preset storage location, and adjusting an index corresponding to the secondary factor A strategy in which preset adjustment strategies corresponding to different indicators are respectively stored in advance, and the adjustment priority of the main factor is higher than the adjustment priority of the secondary factor; and then in the order of adjustment priority from high to low, Use the adjustment strategy of the corresponding index of the main factor in order to adjust the corresponding index of the main factor, and use the adjustment strategy of the corresponding index of the found secondary factor to adjust the corresponding index of the secondary factor, so that the index of the index fund The tracking error is less than a preset tracking error threshold. The preset tracking error threshold can be configured in advance according to actual needs.

Through the above-mentioned way of automatically querying the corresponding adjustment schemes for each indicator, and then performing the adjustment in a timely manner, the purpose of accurate adjustment and rapid adjustment can be achieved, and the most suitable adjustment strategy is used for targeted adjustment. And in accordance with the order of adjustment priority from high to low, priority adjustment of the index data corresponding to the main factor, and then adjustment of the index data corresponding to the secondary factor can speed up the adjustment effect of the index tracking error. Compared with the current prior art, the technical solution of this embodiment not only improves the accuracy and efficiency of index tracking error analysis, but also enables timely and accurate adjustments in the intraday market to ensure that index funds track the index as completely as possible.

Further, as a specific implementation of the method in FIG. 1, an embodiment of the present application provides an index tracking error analysis device. As shown in FIG. 3, the device includes: an obtaining unit 31, a determination unit 32, and an analysis unit 33.

The obtaining unit 31 may be used to obtain information data corresponding to the index fund; the obtaining unit 31 is a main functional module for obtaining information data in the device.

The determining unit 32 may be configured to determine index data of the index fund according to the information data obtained by the obtaining unit 31, where the index data includes an alpha coefficient index, a beta coefficient index, a maximum retracement index, and an annualized return rate of the index fund The index, the cumulative return index, and the value-at-risk VAR parameter index; the determining unit 32 is a main function module for determining fund index data and an index tracking error analysis result in the device.

The analysis unit 33 may be used to analyze the index data determined by the determination unit to obtain the return error cause information and risk error cause information of the index fund; the analysis unit 33 is a main functional module for analyzing the fund return error cause and the risk error cause in the device .

The determining unit 32 may be further configured to determine an analysis result of the index tracking error of the index fund according to the return error cause information and risk error cause information analyzed by the analysis unit 33.

In a specific application scenario, the analysis unit 33 may be specifically configured to separately calculate the first deviation error between each indicator in the indicator data and the respective preset target value; and multiply the first deviation error corresponding to each indicator by each corresponding And the sum of the predetermined weights of each index; divide the first deviation error of each indicator by the sum to obtain the first deviation error ratio of each indicator; select the first deviation error ratio greater than the preset ratio The index whose sum error is greater than the threshold and / or the deviation is larger than the first preset deviation threshold is used as the first index to be analyzed; the covariance matrix is used to calculate the first index to be analyzed and other indexes except the first index to be analyzed. The correlation between the first to be analyzed index and the index with a strong correlation with the first to be analyzed index is determined as the first major error factor affecting the return error of the index fund.

In a specific application scenario, the analysis unit 33 can also be specifically used to calculate the expected deviation error value of each indicator according to the second deviation error of each indicator during the historical period; select a second deviation error greater than the corresponding deviation The index of the expected error value and / or the second deviation error is greater than the second predetermined deviation error threshold, as the second index to be analyzed, wherein the second predetermined deviation threshold is set in advance according to the anti-risk factor of the index fund; the covariance matrix is used to calculate Correlation between the second indicator to be analyzed and indicators other than the second indicator to be analyzed; determine the second indicator to be analyzed and the indicator with a strong correlation with the second indicator to be analyzed as the impact The second major error factor for the risk error of index funds.

In a specific application scenario, the determining unit 32 may be specifically configured to determine the same factor existing in the first major error factor and the second major error factor as the main factor affecting the index tracking error of the index fund, and A difference factor between a major error factor and a second major error factor is determined as a minor factor affecting the index tracking error of the index fund.

In a specific application scenario, as shown in FIG. 4, the device further includes: a query unit 34 and an adjustment unit 35;

The query unit 34 may be used to query an adjustment strategy corresponding to the index corresponding to the main factor from a preset storage location, and an adjustment strategy corresponding to the index corresponding to the secondary factor. The preset storage location stores adjustment strategies corresponding to different indicators, of which the main The adjustment priority of factors is higher than the adjustment priority of secondary factors;

The adjustment unit 35 may be used to adjust the corresponding index of the main factor in accordance with the order of the adjustment priority from the highest to the lowest, and then adjust the corresponding index of the main factor, and adjust the corresponding index of the used secondary factor. Strategy to adjust the corresponding index of the secondary factor so that the index tracking error of the index fund is less than the preset tracking error threshold.

In a specific application scenario, the determining unit 32 may also be specifically configured to calculate the overall market return rate of the index fund x based on the closing number of the latest index period corresponding to the index fund and the closing number of the previous period period, and Based on the closing price of the latest period of each stock under the index fund and the closing price of the previous period, calculate the yield y of each stock under the index fund; use the formula COV (x, y) / VAR (x) Calculate the β coefficient of each stock affected by the capital structure of the index fund, and use the formula COV (x, y) / VAR (x) / (1+ (1-T) * D / E) to calculate the β coefficient of the index fund. The β coefficient of the stock structure without the impact of capital structure, where T is the income tax rate of the company corresponding to the stock; D is the market value of the company's debt for the stock; E is the market value of the company's equity for the stock;

In a specific application scenario, the determining unit 32 may also be specifically used to calculate a product of COV (x, y) / VAR (x) and a profit value of a predetermined length of investment index funds based on a predetermined amount of funds, and convert the index type The absolute return of the fund minus the product to obtain the alpha coefficient of the index fund, where the absolute return of the index fund is the difference between the profit value minus the risk-free investment income of the predetermined amount of funds corresponding to a preset duration.

In a specific application scenario, the determining unit 32 may also be specifically used to divide the internal investment return of an index fund by the principal, then divide it by the number of investment days, then multiply by the total number of days in a year, and then multiply by 100% to obtain the index Annualized return of fund;

In a specific application scenario, the determining unit 32 may also be specifically used to calculate the VAR parameter of the index fund by using the formula M (ΔMΔt ≦ VaR) = N, where M is the asset value loss of the index fund is less than a preset The probability of the upper limit of loss, ΔM is the value loss of the index fund during a certain holding period Δt, and VaR is the value at risk at a predefined confidence level N.

It should be noted that, for other corresponding descriptions of the functional units involved in the exponential tracking error analysis device provided in the embodiment of the present application, reference may be made to the corresponding descriptions in FIG. 1 and FIG. 2, and details are not described herein again.

Based on the method shown in FIG. 1 and FIG. 2, correspondingly, an embodiment of the present application further provides a non-volatile readable storage medium having computer-readable instructions stored thereon. Implementation of the above-mentioned exponential tracking error analysis method shown in Figures 1 and 2 is implemented.

Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a U disk, a mobile hard disk, etc.), including several The instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of this application.

Based on the method shown in FIG. 1 and FIG. 2 and the embodiments of the virtual device shown in FIG. 3 and FIG. 4, in order to achieve the foregoing objective, an embodiment of the present application further provides a computer device, which may specifically be a personal computer, A server, a network device, etc., the physical device includes a non-volatile readable storage medium and a processor; a non-volatile readable storage medium for storing computer-readable instructions; a processor for executing computer-readable instructions to The above-mentioned exponential tracking error analysis method shown in Figs. 1 and 2 is implemented.

Optionally, the computer device may further include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, and the like. The user interface may include a display, an input unit such as a keyboard, etc. The optional user interface may also include a USB interface, a card reader interface, and the like. The network interface may optionally include a standard wired interface, a wireless interface (such as a Bluetooth interface, a WI-FI interface), and the like.

Those skilled in the art can understand that a computer device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or arrange different components.

The storage medium may further include an operating system and a network communication module. An operating system is computer-readable instructions that manage the hardware and software resources of the computer device, and supports the operation of information-processing computer-readable instructions and other software and / or computer-readable instructions. The network communication module is used to implement communication between components in the storage medium, and communication with other hardware and software in the physical device.

Through the description of the above embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary universal hardware platform, or by hardware. By applying the technical solution of the present application, compared with the current prior art, not only the accuracy and efficiency of index tracking error analysis is improved, but also timely and accurate adjustments can be achieved to ensure that index funds track the index as completely as possible.

Those skilled in the art can understand that the accompanying drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required to implement this application. Those skilled in the art can understand that the modules in the device in the implementation scenario may be distributed among the devices in the implementation scenario according to the description of the implementation scenario, or may be correspondingly located in one or more devices different from the implementation scenario. The modules of the above implementation scenario can be combined into one module, or further divided into multiple sub-modules.

The above serial number of this application is only for description, and does not represent the advantages and disadvantages of the implementation scenario. The above disclosure is only a few specific implementation scenarios of this application, but this application is not limited to this, and any changes that can be thought by those skilled in the art should fall into the protection scope of this application.

Claims

An exponential tracking error analysis method, comprising:

Obtaining information and data corresponding to index funds;

Determining the index data of the index fund according to the information data, wherein the index data includes an α coefficient index, a β coefficient index, a maximum retracement index, an annualized return index, and an accumulated return rate of the index fund Indicators, value-at-risk VAR parameter indicators;

Analyze the index data to obtain the return error cause information and risk error cause information of the index fund;

An analysis result of the index tracking error of the index fund is determined according to the return error cause information and the risk error cause information.
The method according to claim 1, wherein analyzing the reason information of the return error of the index fund through the index data specifically comprises:

Respectively calculating a first deviation error between each indicator in the indicator data and a respective preset target value;

Respectively multiplying the first deviation errors corresponding to the indicators by respective corresponding predetermined weights and adding them to obtain a sum value;

Divide the first deviation error of each indicator by the sum value to obtain the first deviation error proportion of each indicator;

Selecting, as the first index to be analyzed, an index where the first deviation error ratio is greater than a preset ratio threshold and / or the first deviation error is greater than a first preset deviation threshold;

Using a covariance matrix to calculate an association relationship between the first index to be analyzed and other indexes among the indexes except the first index to be analyzed;

The first to-be-analyzed indicator and the indicator having a strong correlation with the first to-be-analyzed indicator are determined as the first major error factor that affects the return error of the index fund.
The method according to claim 2, wherein analyzing the risk error cause information of the index fund through the index data specifically includes:

Calculate the expected deviation error value of each indicator according to the second deviation error of each indicator in the historical period;

An index that has a second deviation error greater than a corresponding deviation error expected value and / or a second deviation error greater than a second predetermined deviation threshold is selected as the second to-be-analyzed index, wherein the second predetermined deviation threshold is in accordance with the index fund Anti-risk factors are set in advance;

Using a covariance matrix to calculate an association relationship between the second index to be analyzed and other indexes among the indexes except the second index to be analyzed;

The second to-be-analyzed indicator and an indicator having a strong correlation with the second to-be-analyzed indicator are determined as the second major error factor that affects the risk error of the index fund.
The method according to claim 3, wherein determining an index tracking error analysis result of the index fund according to the return error cause information and the risk error cause information specifically includes:

Determining the first main error factor and the same factor existing in the second main error factor as the main factors affecting the index tracking error of the index fund, and comparing the first main error factor with the The difference factor between the second main error factors is determined as a secondary factor that affects the index tracking error of the index fund.
The method according to claim 4, further comprising:

Query the adjustment strategy of the index corresponding to the main factor and the adjustment strategy of the index corresponding to the secondary factor from a preset storage location. The preset storage location stores adjustment strategies corresponding to different indicators, among which The adjustment priority of the major factor is higher than the adjustment priority of the minor factor;

According to the order of the adjustment priority from high to low, the adjustment strategy of the corresponding index of the main factor is used in turn to adjust the corresponding index of the main factor, and the corresponding index of the secondary factor is used. The adjustment strategy is to adjust the index corresponding to the secondary factor so that the index tracking error of the index fund is smaller than a preset tracking error threshold.
The method according to claim 1, wherein determining the beta coefficient index of the index fund according to the information data specifically includes:

Calculate the overall market return rate x of the index fund according to the closing number of the latest period corresponding to the index fund and the closing number of the previous period, and according to the latest one of the stocks of the index fund The closing price at the end of the period and the closing price at the end of the previous period, calculate the yield y of each stock under the index fund;

Use the formula COV (x, y) / VAR (x) to calculate the β coefficient of each stock under the index fund affected by the capital structure, and use the formula COV (x, y) / VAR (x) / (1+ ( 1-T) * D / E) Calculate the β coefficient of each stock under the index fund that eliminates the impact of capital structure, where T is the income tax rate of the company corresponding to the stock; D is the market value of the company's debt corresponding to the stock; E is The market value of the stock corresponding to the company's equity;

According to the information data, determining an alpha coefficient index of the index fund specifically includes:

Calculate the product of COV (x, y) / VAR (x) and the value of the profit of the index fund for a predetermined period of time, and subtract the product of the absolute return of the index fund to obtain the product The alpha coefficient of the index fund, wherein the absolute return of the index fund is the difference between the profit value minus the predetermined amount of funds and the risk-free investment income of the preset duration.
The method according to claim 6, wherein determining the annualized rate of return index of the index fund according to the information data specifically includes:

Dividing the internal investment income of the index fund by the principal, dividing it by the number of investment days, multiplying by the total number of days in a year, and then multiplying by 100% to obtain the annualized rate of return of the index fund;

According to the information data, determining the VAR parameter index of the index fund specifically includes:

Use the formula M (ΔMΔt≤VaR) = N to calculate the VAR parameter of the index fund, where M is the probability that the asset value loss of the index fund is less than the preset upper limit of loss, and ΔM is the index fund In a certain holding period Δt, VaR is the value at risk at a predefined confidence level N.
An exponential tracking error analysis device, comprising:

An obtaining unit for obtaining information data corresponding to the index fund;

A determining unit, configured to determine the index data of the index fund according to the information data obtained by the obtaining unit, wherein the index data includes an alpha coefficient index, a beta coefficient index, and a maximum retracement index of the index fund , Annualized return index, cumulative return index, value-at-risk VAR parameter index;

An analysis unit, configured to analyze, through the index data determined by the determination unit, the cause information of the return error and the cause of the risk error of the index fund;

The determining unit is further configured to determine an index tracking error analysis result of the index fund according to the return error cause information and the risk error cause information analyzed by the analysis unit.
The device according to claim 8, characterized in that:

The analysis unit is specifically configured to separately calculate a first deviation error between each indicator in the indicator data and a respective preset target value; and respectively multiply the first deviation error corresponding to each indicator by a corresponding predetermined weight. Divide the first deviation error of each indicator by the sum value to obtain the first deviation error ratio of each indicator; select the first deviation error ratio greater than a preset ratio An index that is greater than a threshold and / or that the first deviation error is greater than a first preset deviation threshold is used as a first index to be analyzed; a covariance matrix is used to calculate the first index to be analyzed and divide each of the indexes Association relationship between indicators other than the first to-be-analyzed indicator; determining the first to-be-analyzed indicator and an indicator with a strong correlation with the first to-be-analyzed indicator as the ones that affect the index fund Returns the first major error factor.
The device according to claim 9, wherein:

The analysis unit is further configured to calculate the expected deviation error value of each indicator according to the second deviation error of the historical period of the indicators by using a normal distribution algorithm; and select the second deviation error that is greater than the corresponding expected deviation error value. And / or an index whose second deviation error is greater than a second predetermined deviation threshold is used as a second indicator to be analyzed, wherein the second predetermined deviation threshold is set in advance according to the anti-risk factor of the index fund; using a covariance matrix, calculation is performed An association relationship between the second to-be-analyzed indicator and other indicators among the indicators except the second to-be-analyzed indicator; and the second to-be-analyzed indicator and the second to-be-analyzed indicator An indicator with a strong correlation is determined as the second major error factor that affects the risk error of the index fund.
The device according to claim 10, wherein:

The determining unit is specifically configured to determine the same main factor existing in the first main error factor and the second main error factor as the main factor that affects the index tracking error of the index fund, and The difference factor between the first major error factor and the second major error factor is determined as a minor factor that affects the index tracking error of the index fund.
The device according to claim 11, further comprising:

The querying unit is configured to query, from a preset storage location, an adjustment strategy corresponding to the index corresponding to the primary factor and an adjustment strategy corresponding to the index corresponding to the secondary factor, and the preset storage location stores respective indexes corresponding to different indicators. An adjustment strategy, wherein the adjustment priority of the primary factor is higher than the adjustment priority of the secondary factor;

An adjustment unit, configured to sequentially adjust the corresponding index of the main factor according to the adjustment order of the adjustment index of the main factor in accordance with the order of the adjustment priority from high to low, and use the inquired query The adjustment strategy of the index corresponding to the secondary factor adjusts the index corresponding to the secondary factor so that the index tracking error of the index fund is smaller than a preset tracking error threshold.
The device according to claim 8, characterized in that:

The determining unit is specifically configured to calculate the overall market return rate x of the index fund according to the closing number of the latest period corresponding to the index fund and the closing number of the previous period, and according to the index The closing price of the latest period of each stock under the fund and the closing price of the previous period, calculate the return rate y of each stock under the index fund; use the formula COV (x, y) / VAR (x) Calculate the β coefficient of each stock under the index fund affected by the capital structure, and calculate the index using the formula COV (x, y) / VAR (x) / (1+ (1-T) * D / E) The β coefficient of each stock under the capital fund to eliminate the impact of capital structure, where T is the income tax rate of the company corresponding to the stock; D is the market value of the company's debt corresponding to the stock; E is the market value of the company's equity corresponding to the stock;

The determining unit is further specifically configured to calculate a product of COV (x, y) / VAR (x) and a profit value of a predetermined duration of investment in the index fund according to a predetermined amount of funds, and calculate an absolute value of the index fund Subtract the product from the return to obtain the alpha coefficient of the index fund, where the absolute return of the index fund is the profit value minus the risk-free investment income of the predetermined amount of funds corresponding to the preset duration The difference.
The device according to claim 13, wherein:

The determining unit is specifically configured to divide the internal investment return of the index fund by the principal, then divide it by the number of investment days, then multiply by the total number of days in a year, and then multiply by 100% to obtain the index fund. Annualized rate of return

The determining unit is further specifically configured to calculate a VAR parameter of the index fund by using a formula M (ΔMΔt ≦ VaR) = N, where M is a loss of an asset value of the index fund less than a preset loss upper limit. Probability, ΔM is the value loss amount of the index fund during a certain holding period Δt, and VaR is the value at risk at a predefined confidence level N.
A non-volatile readable storage medium having computer-readable instructions stored thereon, characterized in that when the computer-readable instructions are executed by a processor, an exponential tracking error analysis method is implemented, including:

Obtaining information data corresponding to the index fund; determining index data of the index fund according to the information data, wherein the index data includes an α coefficient index, a β coefficient index, a maximum retracement index, Annualized return index, cumulative return index, and value-at-risk VAR parameter index; analyze the index data to obtain the return error reason information and risk error cause information of the index fund; according to the return error cause information and the The risk error cause information determines the analysis result of the index tracking error of the index fund.
The non-volatile readable storage medium according to claim 15, wherein when the computer-readable instructions are executed by a processor, the index data is used to analyze the return error cause information of the index fund, These include:

Calculate a first deviation error between each indicator in the indicator data and a respective preset target value; multiply the first deviation error corresponding to each indicator by a respective corresponding predetermined weight, and add up to obtain a sum value Dividing the first deviation error of each indicator by the sum value to obtain the first deviation error ratio of each indicator; selecting the first deviation error ratio to be greater than a preset ratio threshold and / or the first An index whose deviation error is greater than a first preset deviation threshold is used as the first index to be analyzed; using the covariance matrix, calculating the first index to be analyzed and each index other than the first index to be analyzed Association relationship between indicators; determining the first to-be-analyzed indicator and an indicator having a strong correlation with the first to-be-analyzed indicator as the first major error factor affecting the return error of the index fund .
The non-volatile readable storage medium according to claim 16, wherein when the computer-readable instructions are executed by a processor, the index data is used to analyze the risk error cause information of the index fund, These include:

The normal deviation algorithm is used to calculate the expected deviation error of each indicator according to the second deviation error of each indicator in the historical period; and the second deviation error is greater than the corresponding deviation error expected value and / or the second deviation error is greater than the first deviation error. An index of two predetermined deviation thresholds is used as a second to-be-analyzed index, wherein the second predetermined deviation threshold is set in advance according to the anti-risk factor of the index fund; a covariance matrix is used to calculate the second to-be-analyzed index and The association relationship among the indicators other than the second to-be-analyzed indicator is described; the second to-be-analyzed indicator and the indicator having a strong correlation with the second to-be-analyzed indicator are determined as The second major error factor affecting the risk error of the index fund.
A computer device includes a non-volatile readable storage medium, a processor, and computer-readable instructions stored on the non-volatile readable storage medium and executable on the processor, wherein the processor A method for implementing exponential tracking error analysis when executing the computer-readable instructions includes:

Obtaining information data corresponding to the index fund; determining index data of the index fund according to the information data, wherein the index data includes an α coefficient index, a β coefficient index, a maximum retracement index, Annualized return index, cumulative return index, and value-at-risk VAR parameter index; analyze the index data to obtain the return error reason information and risk error cause information of the index fund; according to the return error cause information and the The risk error cause information determines the analysis result of the index tracking error of the index fund.
The computer device according to claim 18, wherein when the processor executes the computer-readable instructions, the analysis of the return error cause information of the index fund through the indicator data specifically includes:

Calculate a first deviation error between each indicator in the indicator data and a respective preset target value; multiply the first deviation error corresponding to each indicator by a respective corresponding predetermined weight, and add up to obtain a sum value Dividing the first deviation error of each indicator by the sum value to obtain the first deviation error ratio of each indicator; selecting the first deviation error ratio to be greater than a preset ratio threshold and / or the first An index whose deviation error is greater than a first preset deviation threshold is used as the first index to be analyzed; using the covariance matrix, calculating the first index to be analyzed and each index other than the first index to be analyzed Association relationship between indicators; determining the first to-be-analyzed indicator and an indicator having a strong correlation with the first to-be-analyzed indicator as the first major error factor affecting the return error of the index fund .
The computer device according to claim 19, wherein the processor, when executing the computer-readable instructions, analyzes the risk error cause information of the index fund through the indicator data, and specifically includes:

The normal deviation algorithm is used to calculate the expected deviation error of each indicator according to the second deviation error of each indicator in the historical period; and the second deviation error is greater than the corresponding deviation error expected value and / or the second deviation error is greater than the first deviation error. An index of two predetermined deviation thresholds is used as a second to-be-analyzed index, wherein the second predetermined deviation threshold is set in advance according to the anti-risk factor of the index fund; a covariance matrix is used to calculate the second to-be-analyzed index and The association relationship among the indicators other than the second to-be-analyzed indicator is described; the second to-be-analyzed indicator and the indicator having a strong correlation with the second to-be-analyzed indicator are determined as The second major error factor affecting the risk error of the index fund.