Application of regression function model based on panel data in financial risk management of bank resource allocation
This paper studies the financial risk management of resource allocation of listed commercial banks in my country, starting from the fundamental influence of lender credit rating in the internal rating system of commercial banks, and analyzes the influence of a large number of subjective factors cont...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2022.2.0097 |
| _version_ | 1797688753438851072 |
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| author | Yang Cheng Hasan Hafnida |
| author_facet | Yang Cheng Hasan Hafnida |
| author_sort | Yang Cheng |
| collection | DOAJ |
| description | This paper studies the financial risk management of resource allocation of listed commercial banks in my country, starting from the fundamental influence of lender credit rating in the internal rating system of commercial banks, and analyzes the influence of a large number of subjective factors contained in the bank’s credit rating system on the rating effect. Influence. A sort-response panel regression function model with random effects (including random intercept terms and random coefficients) is proposed, and the rationality of the existing bank credit rating system is tested and analyzed. The experimental results show that the model’s prediction accuracy rate is 48.27%, and the percentage of prediction level error within two levels reaches 86.8%. The application of this model can find the redundant indicators of the existing system, which are highly fitted with the actual situation and can achieve quite ideal forecasting results, and provide a forecasting reference for the weight setting, which provides a basis for the revision of the bank’s credit rating system. |
| first_indexed | 2024-03-12T01:35:14Z |
| format | Article |
| id | doaj.art-8bb89eb14ea541d9aa7d32def5eeba07 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-12T01:35:14Z |
| publishDate | 2023-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-8bb89eb14ea541d9aa7d32def5eeba072023-09-11T07:01:09ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562023-01-01811849186010.2478/amns.2022.2.0097Application of regression function model based on panel data in financial risk management of bank resource allocationYang Cheng0Hasan Hafnida11YongZhou Vocational Technical College, Yongzhou, 425000, China2College of Administrative Sciences, Applied Science University, BahrainThis paper studies the financial risk management of resource allocation of listed commercial banks in my country, starting from the fundamental influence of lender credit rating in the internal rating system of commercial banks, and analyzes the influence of a large number of subjective factors contained in the bank’s credit rating system on the rating effect. Influence. A sort-response panel regression function model with random effects (including random intercept terms and random coefficients) is proposed, and the rationality of the existing bank credit rating system is tested and analyzed. The experimental results show that the model’s prediction accuracy rate is 48.27%, and the percentage of prediction level error within two levels reaches 86.8%. The application of this model can find the redundant indicators of the existing system, which are highly fitted with the actual situation and can achieve quite ideal forecasting results, and provide a forecasting reference for the weight setting, which provides a basis for the revision of the bank’s credit rating system.https://doi.org/10.2478/amns.2022.2.0097regression functioncredit ratingpanel data modelordinal response modelrandom effects62g08 |
| spellingShingle | Yang Cheng Hasan Hafnida Application of regression function model based on panel data in financial risk management of bank resource allocation Applied Mathematics and Nonlinear Sciences regression function credit rating panel data model ordinal response model random effects 62g08 |
| title | Application of regression function model based on panel data in financial risk management of bank resource allocation |
| title_full | Application of regression function model based on panel data in financial risk management of bank resource allocation |
| title_fullStr | Application of regression function model based on panel data in financial risk management of bank resource allocation |
| title_full_unstemmed | Application of regression function model based on panel data in financial risk management of bank resource allocation |
| title_short | Application of regression function model based on panel data in financial risk management of bank resource allocation |
| title_sort | application of regression function model based on panel data in financial risk management of bank resource allocation |
| topic | regression function credit rating panel data model ordinal response model random effects 62g08 |
| url | https://doi.org/10.2478/amns.2022.2.0097 |
| work_keys_str_mv | AT yangcheng applicationofregressionfunctionmodelbasedonpaneldatainfinancialriskmanagementofbankresourceallocation AT hasanhafnida applicationofregressionfunctionmodelbasedonpaneldatainfinancialriskmanagementofbankresourceallocation |