Default correlation determination method and device, equipment and storage medium

Abstract

The invention discloses a default correlation determination method and device, equipment and a storage medium, and relates to the technical field of finance, and the method comprises the steps: obtaining market data of an initial year; performing denoising processing on the initial annual market data to obtain a total market value of a target company; calculating company asset correlation according to the total market value of the target company; the company default correlation is determined according to the company asset correlation, the company asset correlation is calculated through sufficient data on an external financial market, the company default correlation is accurately calculated according to the company asset correlation, and the accuracy of default correlation calculation is improved.

Description

Technical Field

[0001] The present application relates to the field of financial technology, and in particular to a method, device, equipment and storage medium for determining default correlation. Background Art

[0002] The calculation of default correlation is an important part of portfolio management. As a data parameter of the capital measurement engine, the accuracy of the default correlation coefficient directly affects the accuracy of economic capital measurement. Currently, due to the lack of sufficient default data in the industry and the insufficient data completeness of asset management business data, the calculation results of the default correlation model will be constrained to a certain extent, resulting in inaccurate calculation of default correlation. Summary of the invention

[0003] The main purpose of this application is to provide a default correlation determination method, device, equipment and storage medium, aiming to solve the current technical problem of inaccurate default correlation calculation.

[0004] To achieve the above purpose, the present application proposes a default correlation determination method, which includes:

[0005] Obtain initial annual market data;

[0006] De-noising the initial annual market data to obtain the total market value of the target company;

[0007] Calculate the company asset relevance based on the total market value of the target company;

[0008] The company default correlation is determined based on the company asset correlation.

[0009] In one embodiment, the step of performing denoising on the initial annual market data to obtain the total market value of the target company includes:

[0010] determining whether overall denoising is required based on the initial annual market data;

[0011] When the initial annual market data needs to be subjected to overall denoising, the initial annual market data is subjected to overall denoising to obtain an adjusted total market value of the company;

[0012] Obtain a denoising adjustment coefficient according to the adjusted total market value of the company;

[0013] The adjusted total market value of the company is individually denoised using the denoising adjustment coefficient to obtain the total market value of the target company.

[0014] In one embodiment, when the annual market data needs to be subjected to overall denoising, the step of performing overall denoising on the annual market data to obtain the adjusted total market value of the company includes:

[0015] When the initial annual market data needs to be generally denoised, the company's annual financial indicator data and the company's total market value data are obtained according to the initial annual market data;

[0016] Screening the annual financial indicator data of the company and the total market value data of the company according to data integrity and industry to which they belong, to obtain the annual financial indicator data of the screened company and the total market value data of the screened company;

[0017] Calculate the annual valuation multiple based on the annual financial indicator data of the screened companies and the total market value data of the screened companies;

[0018] Calculate the mean valuation multiple and the standard deviation of the valuation multiple based on the stated annual valuation multiples;

[0019] Calculating an adjustment factor based on the mean of the valuation multiples and the standard deviation of the valuation multiples;

[0020] The adjusted total market value of the company is calculated using the adjustment coefficient and the total market value data of the company.

[0021] In one embodiment, the step of obtaining a denoising adjustment coefficient according to the adjusted total market value of the company includes:

[0022] Get company type;

[0023] Determine the corresponding profitability indicator according to the type of company;

[0024] A denoising adjustment coefficient is calculated based on the profitability indicator and the adjusted total market value of the company.

[0025] In one embodiment, the step of calculating the company asset relevance based on the total market value of the target company includes:

[0026] According to the total market value of the target company, the total market value of the target company at the previous moment and the total market value of the target company at the current moment are obtained;

[0027] Calculate the asset value change rate by using the total market value of the target company at the previous moment and the total market value of the target company at the current moment;

[0028] Calculating the average change rate data of multiple companies through the asset value change rate, and obtaining the asset value change rate data of multiple companies;

[0029] Calculate the correlation coefficient data between the companies based on the average change rate data and the asset value change rate data;

[0030] The company asset correlation is obtained based on the correlation coefficient data.

[0031] In one embodiment, the step of determining the company default correlation according to the company asset correlation comprises:

[0032] constructing an asset correlation matrix based on the asset correlations of the companies;

[0033] Selecting a target grouping dimension through the asset correlation matrix;

[0034] Calculating the default probability of each group under the target grouping dimension through the target grouping dimension;

[0035] The company default correlation is determined based on the default probability and the asset correlation matrix.

[0036] In one embodiment, the step of determining the company default correlation according to the default probability and the asset correlation matrix comprises:

[0037] Obtaining a first cumulative distribution function, a first inverse cumulative distribution function, and a second cumulative distribution function;

[0038] Calculate a joint default probability based on the first cumulative distribution function, the first inverse cumulative distribution function, the second cumulative distribution function, the default probability, and the asset correlation matrix;

[0039] Calculating a default correlation coefficient based on the joint default probability and the default probability;

[0040] The company default correlation is obtained according to the default correlation coefficient.

[0041] In addition, to achieve the above purpose, the present application also proposes a default correlation determination device, the default correlation determination device comprising:

[0042] Acquisition module, used to obtain initial annual market data;

[0043] A processing module, used for performing denoising on the initial annual market data to obtain the total market value of the target company;

[0044] A calculation module, used for calculating the company asset relevance according to the total market value of the target company;

[0045] A determination module is used to determine the company's default correlation based on the company's asset correlation.

[0046] In addition, to achieve the above-mentioned purpose, the present application also proposes a default correlation determination device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the default correlation determination method as described above.

[0047] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the default correlation determination method described above are implemented.

[0048] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the default correlation determination method as described above are implemented.

[0049] One or more technical solutions proposed in this application obtain initial annual market data; perform denoising on the initial annual market data to obtain the total market value of the target company; calculate the company asset correlation based on the total market value of the target company; determine the company default correlation based on the company asset correlation, calculate the company asset correlation through relatively sufficient data in the external financial market, and accurately calculate the company default correlation based on the company asset correlation, thereby improving the accuracy of default correlation calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0052] Figure 1 A flowchart diagram of the first embodiment of the method for determining the relevance of default of this application is provided;

[0053] Figure 2 A flow chart of the second embodiment of the method for determining the relevance of default of this application;

[0054] Figure 3 A flowchart diagram of the third embodiment of the method for determining the relevance of default of this application;

[0055] Figure 4 This is a schematic diagram of the overall process of calculating asset correlation in the first embodiment of the default correlation determination method of the present application;

[0056] Figure 5 A flowchart diagram of the fourth embodiment of the method for determining the relevance of default of this application is provided;

[0057] Figure 6This is a schematic diagram of the module structure of the device for determining the default correlation according to an embodiment of the present application;

[0058] Figure 7 Schematic diagram of the device structure of the hardware operating environment involved in the default correlation determination method in the embodiment of the present application.

[0059] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0060] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0061] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0062] The main solution of the embodiment of the present application is: obtaining initial annual market data; denoising the initial annual market data to obtain the total market value of the target company; calculating the company asset correlation based on the total market value of the target company; and determining the company default correlation based on the company asset correlation.

[0063] Due to the lack of sufficient default data in existing technologies and the insufficient data completeness of asset management business data, the calculation of default correlation is not accurate enough.

[0064] The present application provides a solution, which includes obtaining initial annual market data; performing denoising processing on the initial annual market data to obtain the total market value of the target company; calculating the company asset correlation based on the total market value of the target company; and determining the company default correlation based on the company asset correlation.

[0065] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a default correlation determination device, etc. The following takes the default correlation determination device as an example to illustrate this embodiment and the following embodiments.

[0066] Based on this, the present application embodiment provides a method for determining default correlation, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the method for determining default relevance of the present application.

[0067] In this embodiment, the default correlation determination method includes steps S10 to S40:

[0068] Step S10: Obtain initial annual market data.

[0069] It should be noted that the initial annual market data is external public market data, which may include WIND data and BLOOMBERG data, and can be obtained through the WIND database and the BLOOMBERG database. As shown in Table 1, Table 1 is the specific indicators of all A-share listed companies in the Chinese market data of the initial annual market data, including data category, scope, data field, type, frequency, data source and example. The data category is Chinese market data, the scope is all A-share listed companies, the data fields include data time, stock code, total market value, EBITDA (financial indicator), book liabilities, types include date, character, value, frequency is annual or monthly, the data source is the WIND database, and the example can be a specific date, character or value.

[0070] As shown in Table 2, Table 2 is the specific indicators of A-share listed companies in the real estate and construction industries in the Chinese market data of the initial annual market data, including data category, scope, data field, type, frequency, data source and examples. The data category is Chinese market data, the scope is A-share listed companies in the real estate and construction industries, and the data fields include data time, securities code, and cash inflow from operating activities.

[0071] Table 1

[0072]

[0073] Table 2

[0074]

[0075] Table 3

[0076]

[0077] As shown in Table 3, Table 3 is the specific indicators of all Chinese A-share listed companies in the CSRC industry classification data of A-share listed companies in the initial annual market data, including data category, scope, data field, type, frequency, data source and example. The data category is the CSRC industry classification data of A-share listed companies, the scope is all Chinese A-share listed companies, the data fields include stock code, CSRC industry classification-category, CSRC industry classification-major category, industry regrouping, the type is character, the frequency is the latest, the data sources include WIND database and automatically generated according to category industry, major industry and industry regrouping rules, and the examples can be specific dates, sources (real estate development and operation, manufacturing-heavy industry), etc.

[0078] Table 4

[0079]

[0080] As shown in Table 4, Table 4 is the specific indicators of the data of all constituent stocks of the US Russell 3000 Index in the US market data of the initial annual market data, including data category, range, data field, type, frequency, data source and example. The data category is US market data, the range is the data of all constituent stocks of the US Russell 3000 Index, the data fields include data time, securities code, stock price, number of stocks and EBITDA, the types include date, character and value, and the data source is the BLOOMBERG database.

[0081] As shown in Table 5, Table 5 is the specific indicators of the data of all constituent stocks of the US Russell 3000 Index in the BICS industry classification data of the initial annual market data, including data category, range, data field, type, frequency, data source and example. The data category is BICS industry classification data, the range is the data of all constituent stocks of the US Russell 3000 Index, the data fields include IBICS industry classification-INDUSTRY_SECTOR, IBICS industry classification-INDUSTRY_GROUP and BICS industry classification-INDUSTRY_SUBGROUP, the category is character, the frequency is latest, and the data source is BLOOMBERG database.

[0082] Table 5

[0083]

[0084] Based on factors such as the accuracy of financial data, the frequency of market data can generally be selected as "annual". For market data, if there is missing sample data, the average of the most recent data before and after is used to complete it. For example, listed company A is missing the total market value in 2008, and the total market value in 2007 and 2009 is 〖EP〗_2007 and 〖EP〗_2009 respectively, then the total market value in 2008 is 〖EP〗_2008=(〖EP〗_2007+〖EP〗_2009)÷2. Listed company A is missing its total market value in 2008 and 2009, while its total market value in 2007 and 2010 are 〖EP〗_2007 and 〖EP〗_2010 respectively. The total market value in 2008 is 〖EP〗_2008=(〖EP〗_2007+〖EP〗_2010)÷2. After completing the total market value in 2008, the total market value in 2009 is 〖EP〗_2009=(〖EP〗_2008+〖EP〗_2010)÷2.

[0085] Step S20: De-noising the initial annual market data to obtain the total market value of the target company.

[0086] It should be noted that the denoising of the initial annual market data includes overall denoising and individual denoising. Whether to perform individual denoising can be determined based on the selected calculation method.

[0087] By denoising the initial annual time data, the denoised data is obtained, namely the total market value of the target company.

[0088] Step S30: Calculate the company asset relevance according to the total market value of the target company.

[0089] In a specific implementation, the company asset correlation may be calculated based on the total market value of the target company. For example, the change rate of the company asset market value may be calculated based on the total market value of the target company, thereby calculating the company asset correlation.

[0090] Step S40: Determine the company default correlation according to the company asset correlation.

[0091] It is understandable that the asset correlation matrix can be determined based on the company's asset correlation. When calculating the company's default correlation, it is necessary to import the asset correlation matrix, that is, the output result of the asset correlation function module. At this time, the dimension of the default correlation is consistent with the dimension of the asset correlation, so the "correlation calculation" function is called according to the asset correlation dimension to calculate the default probability of each group under the grouping dimension, so as to calculate the joint default probability according to the asset correlation and the default probability, and then calculate the default correlation.

[0092] After calculating the company default correlation, the company default correlation can be used to assess the company's default risk and help credit rating agencies determine the company's credit rating. Default correlation can also be used to assess and manage the credit risk of companies in the investment portfolio. Risk early warning systems can also be built through company default correlation to identify potential risks in advance by monitoring changes in default correlation.

[0093] This embodiment provides a method for determining default correlation, which includes obtaining initial annual market data; performing denoising processing on the initial annual market data to obtain the total market value of the target company; calculating the company asset correlation based on the total market value of the target company; determining the company default correlation based on the company asset correlation, calculating the company asset correlation through relatively sufficient data in the external financial market, and accurately calculating the company default correlation based on the company asset correlation, thereby improving the accuracy of the default correlation calculation.

[0094] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S20 includes steps S201 to S204:

[0095] Step S201: determining whether overall denoising is required based on the initial annual market data.

[0096] It should be noted that, for example, an overall denoising threshold or an overall denoising rule is set to determine whether the initial annual market data meets the overall denoising threshold or the overall denoising rule. If so, it is determined that the initial annual market data needs to be denoised overall; if not, it is determined that the initial annual market data needs to be denoised overall.

[0097] Step S202: When the initial annual market data needs to be subjected to overall denoising, the initial annual market data is subjected to overall denoising to obtain an adjusted total market value of the company.

[0098] It should be noted that when the initial annual market data needs to be overall denoised, the initial annual market data can be overall denoised to obtain the adjusted total market value of the company.

[0099] In a feasible implementation, step S202 may include steps A10 to A15:

[0100] Step A10: When the initial annual market data needs to be generally denoised, the company's annual financial indicator data and the company's total market value data are obtained according to the initial annual market data.

[0101] It should be noted that when the annual market data needs to be generally denoised, the total annual series of market capitalization and EBITDA of the Chinese market and Russell 3000 constituent stocks can be calculated based on the initial annual time data, thereby obtaining the company's annual financial indicator data and the company's total market value data.

[0102] Step A11: Filter the company's annual financial indicator data and the company's total market value data according to data integrity and industry to which they belong, to obtain the filtered company's annual financial indicator data and the filtered company's total market value data.

[0103] In specific implementation, the annual financial indicator data and the total market value data of the company can be screened according to data integrity and the industry to which the company belongs. By obtaining the annual EBITDA and total market value data of all A-share listed companies, the annual EBITDA, year-end stock count, and year-end stock price data of the Russell 3000 components in the United States, the annual total market value of the Russell 3000 components can be calculated using the year-end stock price of the Russell 3000 components × the year-end stock count.

[0104] If there are EBITDA and total market value data in both the sample start year and the sample end year and the company is a non-financial industry company, it will be retained. Among them: domestic listed companies whose industry is financial industry in the CSRC industry classification category are financial industry companies, and Russell 3000 constituent companies whose INDUSTRY_GROUP is "Diversified Finan Serv", "Banks" or "Insurance", "Investment Companies" in the BICS industry classification are financial industry companies. Thus, the annual financial indicator data and total market value data of the screened companies are obtained.

[0105] Step A12: Calculate the annual valuation multiple based on the annual financial indicator data of the screened companies and the total market value data of the screened companies.

[0106] It is understandable that the annual valuation multiple can be calculated based on the annual financial indicator data of the screened companies and the total market value data of the screened companies, as shown in Formula 1:

[0107] Annual valuation multiple = total market value of the screening company / annual financial indicators of the screening company (Formula 1)

[0108] Step A13: Calculate the mean valuation multiple and the standard deviation of the valuation multiple based on the annual valuation multiple.

[0109] In specific implementation, the annual valuation multiples of all industries and all companies can be obtained, so that the mean valuation multiples and the standard deviation of the annual valuation multiples can be calculated.

[0110] In specific implementation, the adjusted valuation multiple of China's stock market = (the valuation multiple of the domestic stock market before adjustment - the average valuation multiple of the domestic stock market) ÷ the standard deviation of the domestic stock market before adjustment × the standard deviation of the domestic stock market after adjustment + the average valuation multiple of the domestic stock market.

[0111] The adjusted standard deviation of the domestic stock market can be used to calculate the valuation multiple standard deviation based on the Chinese stock market mean, the U.S. duration coefficient of variation and the overall denoising multiple. The adjusted standard deviation of the domestic stock market = the Chinese stock market mean × the U.S. market coefficient of variation × the overall denoising multiple.

[0112] Step A14: Calculate the adjustment coefficient based on the mean of the valuation multiples and the standard deviation of the valuation multiples.

[0113] It should be understood that the adjustment factor can be calculated based on the mean and standard deviation of the valuation multiples, as shown in Formula 2 below:

[0114] Adjustment factor = standard deviation of valuation multiples / mean of valuation multiples (Formula 2)

[0115] As an example, the adjustment factor = the adjusted valuation multiple of the Chinese stock market / the annual valuation multiple before adjustment.

[0116] Step A15: Calculate the adjusted total market value of the company using the adjustment coefficient and the company's total market value data.

[0117] It should be noted that the adjusted equity market value of each listed company each year can be calculated using the adjustment coefficient. For example, if the adjustment coefficient is 1.06, then the adjusted total market value of the company = the company's total market value data × 1.06.

[0118] Step S203: Obtain a denoising adjustment coefficient according to the adjusted total market value of the company.

[0119] It should be noted that the calculation method used to determine the company's asset correlation and company default correlation is that if the calculation method of the pre-adjustment market value is selected, individual denoising is not required. If the adjusted market value method is selected, individual denoising is required. Therefore, the denoising adjustment coefficient can be obtained by calculating the total market value of the company after adjustment.

[0120] The denoising adjustment coefficient is the individual denoising adjustment coefficient of each secondary industry (major industry). It can be calculated by calculating the profitability indicators of the companies in each secondary industry in the year, and calculating the denoising adjustment coefficient through the profitability indicators and the adjusted total market value of the company.

[0121] In a feasible implementation, step S203 may include steps A20 to A22:

[0122] Step A20: Get the company type.

[0123] It should be noted that companies can be classified in advance according to the industry to which they belong, for example, by classifying companies according to the national standard industry classification, thereby obtaining different types of companies.

[0124] Step A21: Determine the corresponding profitability indicator according to the company type.

[0125] In specific implementation, the corresponding profitability index can be determined according to the company type. Different types of companies use different indicators as profitability indicators. Specifically: companies with the categories of "K Real Estate Industry" and "E Construction Industry" are classified as real estate companies, and the profitability index can be EBITDA or cash inflow from operating activities. The parameter "Profitability Index of Real Estate Companies" can be set in the parameter setting interface for selection. Companies with the category of "J Financial Industry" are classified as financial institutions, and the profitability index is net profit. Companies that do not belong to the categories of "K Real Estate Industry", "E Construction Industry" and "J Financial Industry" are classified as general companies, and the profitability index is EBITDA.

[0126] Step A22: Calculate a denoising adjustment coefficient based on the profitability indicator and the adjusted total market value of the company.

[0127] In a specific implementation, the sum of profitability indicators can be calculated, and then the denoising adjustment coefficient can be calculated by the sum of profitability indicators and the adjusted total market value of the company, as shown in Formula 3:

[0128] De-noising adjustment coefficient K = adjusted total market value of the company / sum of profitability indicators (Formula 3)

[0129] Step S204: performing individual denoising on the adjusted total market value of the company using the denoising adjustment coefficient to obtain the total market value of the target company.

[0130] In specific implementation, the adjusted total market value of the company can be individually denoised through the denoising adjustment coefficient to obtain the total market value of the target company. For example, if the denoising adjustment coefficient K is greater than the set upper limit value or less than the set lower limit value, then the adjusted total market value of the company in that year = the equity market value of the company before adjustment in that year + the total liabilities of the company in that year. If the adjusted total market value of the company in that year is less than the total liabilities of the company in that year, then the adjusted total market value of the company in that year = the total liabilities of the company in that year.

[0131] You can also calculate the adjusted total market value of the company for the year without using the denoising adjustment coefficient. The adjusted total market value of the company for the year = the company's profit index value for the year × the equity market value corresponding to the unit profit index value + the company's total liabilities for the year.

[0132] This embodiment determines whether overall denoising is required based on the initial annual market data; when overall denoising is required for the initial annual market data, overall denoising is performed on the initial annual market data to obtain an adjusted total market value of the company; a denoising adjustment coefficient is obtained based on the adjusted total market value of the company; individual denoising is performed on the adjusted total market value of the company using the denoising adjustment coefficient to obtain the total market value of the target company, thereby ensuring that the data of each company has been properly denoised and improving the accuracy of default correlation calculation.

[0133] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 , step S30 includes steps S301 to S305:

[0134] Step S301: obtaining the total market value of the target company at the previous moment and the total market value of the target company at the current moment according to the total market value of the target company.

[0135] It should be noted that when calculating the correlation of company assets, the company's asset value change rate can be calculated first. The asset value change rate is related to the company's total market value at different times. Therefore, the total market value of the target company at the previous moment and the total market value of the target company at the current moment can be obtained based on the total market value of the target company.

[0136] Step S302: Calculate the asset value change rate by using the total market value of the target company at the previous moment and the total market value of the target company at the current moment.

[0137] In specific implementation, the asset value change rate can be calculated based on the total market value of the target company at the previous moment and the total market value of the target company at the current moment, as shown in Formula 4:

[0138] Asset value change rate = Ln [total market value of the target company at the current moment / total market value of the target company at the previous moment]

[0139] (Formula 4)

[0140] Step S303: Calculate the average change rate data of multiple companies through the asset value change rate, and obtain the asset value change rate data of multiple companies.

[0141] It should be noted that the average change rate data of multiple companies can be calculated based on the asset value change rate, so as to obtain the average change rate between two companies, and the asset value change rate data of multiple companies can be obtained through the asset value change rate.

[0142] Step S304: Calculate the correlation coefficient data between the companies based on the average change rate data and the asset value change rate data.

[0143] In specific implementation, the correlation coefficient between companies can be calculated based on the average change rate data and the asset value change rate data, and the correlation coefficient data can be summarized. The correlation coefficient is calculated as follows:

[0144]

[0145] In the above formula 5, A it and A jt are the asset market value change rates of company i and company j at time point t, and are the average change rates of company i and company j respectively, and ρ represents the correlation coefficient between the two companies.

[0146] Step S305: Obtain the company asset correlation according to the correlation coefficient data.

[0147] In the specific implementation, the company asset correlation can be obtained based on the correlation coefficient data. According to the industry classification specified by the parameter "grouping dimension", the average value of the intra-group and inter-group correlation coefficients is calculated. The mean intra-group correlation coefficient is calculated. Assuming that the kth group has N k customers, then:

[0148]

[0149] Calculate the mean of the inter-group correlation coefficient, assuming that the kth group has Nk customers, group l has N l customers, then:

[0150]

[0151] The company asset correlation is obtained by calculating through the above formula 6 and formula 7.

[0152] like Figure 4 As shown, Figure 4 This is a schematic diagram of the overall process of calculating asset correlation. By obtaining public market data and selecting a calculation method, if the calculation method is the original market value calculation method, the correlation coefficient is directly calculated and the asset correlation matrix is ​​output. If the calculation method is the adjusted market value method, it is determined whether overall denoising is required. If so, individual denoising is performed after overall denoising. If not, individual denoising is performed directly. After individual denoising, the correlation coefficient is calculated and the asset correlation matrix is ​​output.

[0153] Table 6

[0154] Group Name 1 2 3 4 1 AAgriculture / Forestry / Animal Husbandry / Fishery 40.5％ 7.8％ 39.5％ 26.7％ 2 BMining 7.8％ 31.3％ 7.4％ 14.4％ 3 C Manufacturing 39.5％ 7.4％ 39.4％ 29.5％ 4 D Electricity / heat / gas / water production / supply industry 26.7％ 14.4％ 29.5％ 28.4％ ... ... ... ... ... ...

[0155] As shown in Table 6, Table 6 is an asset correlation matrix, including various groups and corresponding asset correlations.

[0156] This embodiment obtains the total market value of the target company at the previous moment and the total market value of the target company at the current moment based on the total market value of the target company; calculates the asset value change rate through the total market value of the target company at the previous moment and the total market value of the target company at the current moment; calculates the average change rate data of multiple companies through the asset value change rate, and obtains the asset value change rate data of multiple companies; calculates the correlation coefficient data between each company based on the average change rate data and the asset value change rate data; obtains the company asset correlation based on the correlation coefficient data. Based on the calculated correlation coefficient data, the correlation between the changes in the asset values ​​of different companies is analyzed. Based on the results of the correlation analysis, the correlation conclusion of the changes in the company asset values ​​can be drawn, so as to quickly understand the overall market dynamics and the specific performance of individual companies.

[0157] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. Figure 5 , step S40 includes steps S401 to S404:

[0158] Step S401: constructing an asset correlation matrix according to the company's asset correlation.

[0159] It should be noted that the calculated company asset correlations can be summarized to obtain an asset correlation matrix.

[0160] Step S402: Select a target grouping dimension through the asset correlation matrix.

[0161] It should be noted that the target grouping dimension is the grouping dimension selected from the asset correlation matrix, and the optional dimensions are the primary industry, the secondary industry, or the industry grouping according to the mapping rules.

[0162] Step S403: Calculate the default probability of each group under the target grouping dimension through the target grouping dimension.

[0163] In a specific implementation, the default probability of each group under the grouping dimension can be calculated through the determined grouping dimension. Specifically, the default probability of each group under the grouping dimension can be calculated by calling the "correlation calculation" function.

[0164] Step S404: Determine the company default correlation according to the default probability and the asset correlation matrix.

[0165] It should be noted that the default correlation coefficient of each group can be calculated based on the default probability and asset correlation to determine the company's default correlation.

[0166] In a feasible implementation, step S404 may include steps B10 to B13:

[0167] Step B10: Obtain a first cumulative distribution function, a first inverse cumulative distribution function, and a second cumulative distribution function.

[0168] In a specific implementation, the first cumulative distribution function is a cumulative distribution function of a standard normal distribution function, and the second cumulative distribution function is a cumulative distribution function of a standard bivariate normal distribution function.

[0169] Step B11: Calculate the joint default probability based on the first cumulative distribution function, the first inverse cumulative distribution function, the second cumulative distribution function, the default probability and the asset correlation matrix.

[0170] In a specific implementation, the joint default probability may be calculated according to the first cumulative distribution function, the first inverse cumulative distribution function, the second cumulative distribution function, the default probability, and the asset correlation corresponding to the asset correlation matrix, as shown in Formula 8:

[0171]

[0172] PD k and PD j is the default probability of group k and group j, is the correlation between the asset values ​​of group k and group j, N1 represents the first cumulative distribution function, N -1 represents the first inverse cumulative distribution function, and N2 represents the second inverse cumulative distribution function.

[0173] Step B12: Calculate the default correlation coefficient based on the joint default probability and the default probability.

[0174] In a specific implementation, the default correlation coefficient can be calculated based on the joint default probability and the default probability, as shown in Formula 9:

[0175]

[0176] Step B13: Obtain the company default correlation according to the default correlation coefficient.

[0177] It can be understood that after obtaining the default correlation coefficient, the default correlation can be determined based on the default correlation coefficient, and the default correlation can be directly used to analyze and explain the default correlation.

[0178] Table 7

[0179] Group Name 1 2 3 4 1 01Construction and Real Estate 12.68％ 17.78％ 8.13％ 8.58％ 2 02Building transportation and warehousing industry 12.78％ 19.00％ 11.58％ 11.03％ 3 03 Electricity / gas / water production and supply industry 8.13％ 11.58％ 6.89％ 6.57％ 4 04Social Services & Communication and Cultural Industries 8.58％ 11.03％ 6.57％ 10.78％ ... ... ... ... ... ...

[0180] It should be noted that a default correlation matrix can be constructed through default correlation, as shown in Table 7. Table 7 is a default correlation matrix table, including default correlations under different groups.

[0181] In specific implementations, the asset correlation model can also be modified based on historical default data, so that existing customer default data can be more accurately applied to correlation calculations.

[0182] This embodiment constructs an asset correlation matrix based on the company's asset correlation; selects a target grouping dimension through the asset correlation matrix; calculates the default probability of each group under the target grouping dimension through the target grouping dimension; determines the company's default correlation based on the default probability and the asset correlation matrix, and estimates the default correlation through relatively sufficient data in the external financial market. That is, through the estimation of the customer's asset correlation, the customer's default correlation is indirectly obtained based on the assumption that "default is triggered when the customer's asset yield drops to a certain critical value."

[0183] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the method for determining the default relevance of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0184] This application also provides a default correlation determination device, please refer to Figure 6 , the default correlation determining device comprises:

[0185] The acquisition module 10 is used to acquire initial annual market data.

[0186] The processing module 20 is used to perform denoising on the initial annual market data to obtain the total market value of the target company.

[0187] The calculation module 30 is used to calculate the company asset relevance according to the total market value of the target company.

[0188] The determination module 40 is used to determine the company default correlation according to the company asset correlation.

[0189] The default correlation determination device provided by the present application adopts the default correlation determination method in the above embodiment, which can solve the technical problem that the current default correlation calculation is not accurate enough. Compared with the prior art, the beneficial effects of the default correlation determination device provided by the present application are the same as the beneficial effects of the default correlation determination method provided by the above embodiment, and other technical features in the default correlation determination device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0190] In one embodiment, the processing module 20 is further used to determine whether overall denoising is required based on the initial annual market data; when overall denoising is required for the initial annual market data, overall denoising is performed on the initial annual market data to obtain an adjusted total market value of the company; a denoising adjustment coefficient is obtained based on the adjusted total market value of the company; and individual denoising is performed on the adjusted total market value of the company using the denoising adjustment coefficient to obtain the total market value of the target company.

[0191] In one embodiment, the processing module 20 is also used to obtain the company's annual financial indicator data and the company's total market value data based on the initial annual market data when the initial annual market data needs to be generally denoised; screen the company's annual financial indicator data and the company's total market value data according to data integrity and the industry to which they belong to obtain the screened company's annual financial indicator data and the screened company's total market value data; calculate the annual valuation multiples based on the screened company's annual financial indicator data and the screened company's total market value data; calculate the valuation multiple mean and the valuation multiple standard deviation based on the annual valuation multiples; calculate the adjustment coefficient based on the valuation multiple mean and the valuation multiple standard deviation; and calculate the adjusted company's total market value through the adjustment coefficient and the company's total market value data.

[0192] In one embodiment, the processing module 20 is further used to obtain a company type; determine a corresponding profitability indicator according to the company type; and calculate a denoising adjustment coefficient according to the profitability indicator and the adjusted total market value of the company.

[0193] In one embodiment, the calculation module 30 is also used to obtain the total market value of the target company at the previous moment and the total market value of the target company at the current moment based on the total market value of the target company; calculate the asset value change rate through the total market value of the target company at the previous moment and the total market value of the target company at the current moment; calculate the average change rate data of multiple companies through the asset value change rate, and obtain the asset value change rate data of multiple companies; calculate the correlation coefficient data between each company based on the average change rate data and the asset value change rate data; and obtain the company asset correlation based on the correlation coefficient data.

[0194] In one embodiment, the determination module 40 is further used to construct an asset correlation matrix based on the company's asset correlation; select a target grouping dimension through the asset correlation matrix; calculate the default probability of each group under the target grouping dimension through the target grouping dimension; and determine the company's default correlation based on the default probability and the asset correlation matrix.

[0195] In one embodiment, the determination module 40 is also used to obtain a first cumulative distribution function, a first inverse cumulative distribution function and a second cumulative distribution function; calculate the joint default probability based on the first cumulative distribution function, the first inverse cumulative distribution function, the second cumulative distribution function, the default probability and the asset correlation matrix; calculate the default correlation coefficient based on the joint default probability and the default probability; and obtain the company default correlation based on the default correlation coefficient.

[0196] The present application provides a default correlation determination device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the default correlation determination method in the above-mentioned embodiment one.

[0197] Reference below Figure 7 , which shows a schematic diagram of the structure of a default correlation determination device suitable for implementing the embodiment of the present application. The default correlation determination device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7The default correlation determination device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0198] like Figure 7 As shown, the default correlation determination device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the default correlation determination device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the default correlation determination device to communicate with other devices wirelessly or by wire to exchange data. Although the default correlation determination device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0199] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0200] The default correlation determination device provided by the present application adopts the default correlation determination method in the above embodiment, which can solve the technical problem that the current default correlation calculation is not accurate enough. Compared with the prior art, the beneficial effects of the default correlation determination device provided by the present application are the same as the beneficial effects of the default correlation determination method provided by the above embodiment, and other technical features in the default correlation determination device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0201] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0202] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0203] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the default correlation determination method in the above-mentioned embodiment.

[0204] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0205] The computer-readable storage medium may be included in the default correlation determination device; or may exist independently without being assembled into the default correlation determination device.

[0206] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the default correlation determination device, the default correlation determination device enables the device to: obtain initial annual market data; perform denoising processing on the initial annual market data to obtain the total market value of the target company; calculate the company asset correlation based on the total market value of the target company; and determine the company default correlation based on the company asset correlation.

[0207] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0208] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0209] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0210] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned default correlation determination method, and can solve the current technical problem that the default correlation calculation is not accurate enough. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the default correlation determination method provided in the above-mentioned embodiment, and will not be repeated here.

[0211] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned default correlation determination method when executed by a processor.

[0212] The computer program product provided by this application can solve the current technical problem that the default correlation calculation is not accurate enough. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the default correlation determination method provided by the above embodiment, which will not be repeated here.

[0213] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for determining default relevance, characterized in that: The default correlation determination method comprises: Obtain initial annual market data; De-noising the initial annual market data to obtain the total market value of the target company; Calculate the company asset relevance based on the total market value of the target company; The company default correlation is determined based on the company asset correlation.

2. The method according to claim 1, characterized in that The step of performing denoising on the initial annual market data to obtain the total market value of the target company comprises: determining whether overall denoising is required based on the initial annual market data; When the initial annual market data needs to be subjected to overall denoising, the initial annual market data is subjected to overall denoising to obtain an adjusted total market value of the company; Obtain a denoising adjustment coefficient according to the adjusted total market value of the company; The adjusted total market value of the company is individually denoised using the denoising adjustment coefficient to obtain the total market value of the target company.

3. The method according to claim 2, characterized in that When the annual market data needs to be subjected to overall denoising, the step of performing overall denoising on the annual market data to obtain the adjusted total market value of the company includes: When the initial annual market data needs to be generally denoised, the company's annual financial indicator data and the company's total market value data are obtained according to the initial annual market data; Screening the annual financial indicator data of the company and the total market value data of the company according to data integrity and industry to which they belong, to obtain the annual financial indicator data of the screened company and the total market value data of the screened company; Calculate the annual valuation multiple based on the annual financial indicator data of the screened companies and the total market value data of the screened companies; Calculate the mean valuation multiple and the standard deviation of the valuation multiple based on the stated annual valuation multiples; Calculating an adjustment factor based on the mean of the valuation multiples and the standard deviation of the valuation multiples; The adjusted total market value of the company is calculated using the adjustment coefficient and the total market value data of the company.

4. The method according to claim 2, characterized in that The step of obtaining the denoising adjustment coefficient according to the adjusted total market value of the company comprises: Get company type; Determine the corresponding profitability indicator according to the type of company; A denoising adjustment coefficient is calculated based on the profitability indicator and the adjusted total market value of the company.

5. The method according to claim 1, characterized in that The step of calculating the company asset relevance according to the total market value of the target company comprises: According to the total market value of the target company, the total market value of the target company at the previous moment and the total market value of the target company at the current moment are obtained; Calculate the asset value change rate by using the total market value of the target company at the previous moment and the total market value of the target company at the current moment; Calculating the average change rate data of multiple companies through the asset value change rate, and obtaining the asset value change rate data of multiple companies; Calculate the correlation coefficient data between the companies based on the average change rate data and the asset value change rate data; The company asset correlation is obtained according to the correlation coefficient data.

6. The method according to claim 1, characterized in that The step of determining the company default correlation according to the company asset correlation comprises: constructing an asset correlation matrix based on the asset correlations of the companies; Selecting a target grouping dimension through the asset correlation matrix; Calculating the default probability of each group under the target grouping dimension through the target grouping dimension; The company default correlation is determined based on the default probability and the asset correlation matrix.

7. The method according to claim 6, characterized in that The step of determining the company default correlation according to the default probability and the asset correlation matrix comprises: Obtaining a first cumulative distribution function, a first inverse cumulative distribution function, and a second cumulative distribution function; Calculate a joint default probability based on the first cumulative distribution function, the first inverse cumulative distribution function, the second cumulative distribution function, the default probability, and the asset correlation matrix; Calculating a default correlation coefficient based on the joint default probability and the default probability; The company default correlation is obtained according to the default correlation coefficient.

8. A device for determining a default correlation, characterized in that: The device comprises: Acquisition module, used to obtain initial annual market data; A processing module, used for performing denoising on the initial annual market data to obtain the total market value of the target company; A calculation module, used for calculating the company asset relevance according to the total market value of the target company; A determination module is used to determine the company's default correlation based on the company's asset correlation.

9. A default correlation determination device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the default relevance determination method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the default correlation determination method according to any one of claims 1 to 7 are implemented.

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