Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 7, Issue 2


Published
on

July 15, 2022


Pages

1849-1860


DOI

Article

Application of regression function model based on panel data in financial risk management of bank resource allocation

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Authors

Cheng Yang Affiliation:
YongZhou Vocational Technical College, Yongzhou, 425000, China
and Hafnida Hasan Affiliation:
College of Administrative Sciences, Applied Science University, Bahrain


Abstract

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.


Keywords

regression function, credit rating, panel data model, ordinal response model, random effects, 62G08


Citation

Yang, C. & Hasan, H. (2022). Application of regression function model based on panel data in financial risk management of bank resource allocation. Applied Mathematics and Nonlinear Sciences, 7(2), 1849–1860. https://doi.org/10.2478/amns.2022.2.0097

Published by: Engineering Journals

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