Interest rate risk of Chinese commercial banks based on the GARCH-EVT model

Xin Chen, Zhangming Shan, Decai Tang (), Biao Zhou and Valentina Boamah
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Xin Chen: Sanjiang University
Zhangming Shan: Nanjing University of Information Science & Technology
Decai Tang: Sanjiang University
Biao Zhou: Nanjing University of Finance and Economics
Valentina Boamah: Nanjing University of Information Science & Technology

Palgrave Communications, 2023, vol. 10, issue 1, 1-11

Abstract: Abstract Interest rate market risk faced by China’s commercial banks is increasing after the announcement that the interest rate marketisation is completed. This paper examines the Value-at-Risk, and statistical properties in the daily price return of Shanghai banks’ overnight offered rate. The study applies two-stage approaches, combining GARCH-type models with extreme value theory. Firstly, the Markov regime switching model is used to test the regime states of the series. Secondly, the performance of different VaR models are examined. Results show that the extreme value approach estimates better at the 99% confidence level. The EGARCH-GED model is the most suitable of the employed GARCH-type models. The back-testing results support the idea that the approach used in this study is appropriate for improving commercial banks’ daily risk management. This paper applies the GARCH-EVT method for interest rate measurement after China’s interest rate marketisation and added regime analysis of interest rate. Suggested policy implications will help formulate policies that guide the activities of commercial banks in China.

Date: 2023
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DOI: 10.1057/s41599-023-02321-6

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