MEASURING SYSTEMIC RISK OF CHINA'S LISTED BANKS

Ping Zhang, Yiru Wang, Min Zhao and Tzu-Yi Yang
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Ping Zhang: Department of Financial Engineering, School of Finance, Capital University of Economics and Business, Beijing, China
Yiru Wang: School of Finance, Capital University of Economics and Business, Beijing, China
Min Zhao: Department of Financial Engineering, School of Finance, Capital University of Economics and Business, Beijing, China
Tzu-Yi Yang: Department of Foreign Languages and Literature National Ilan University, Taiwan

Studii Financiare (Financial Studies), 2021, vol. 25, issue 3, 6-28

Abstract: After the financial crisis in 2008, the world became more aware of the importance of the systemic risk. Within China’s financial system, commercial banks have a dominant position. Therefore, the study of systemic risk of the banking industry in China has an important and real meaning. The present paper was based on the weekly return of 16 listed banks in China from 2010 to 2018. The quantile regression method and the GARCH model were applied to measure the systemic risk of banks in China. The VaR and CoVaR showed that the risk of large commercial banks in China was generally low but was usually higher than the medium and small banks. Comparing the quantile regression method and the GARCH model method indicated that both approaches could effectively measure the systemic risk of listed banks in China. The %CoVAR calculated by the GARCH model was significantly smaller than the result from the quantile regression method. Compared with the DCC-GARCH model, a simple GARCH model might underestimate the systemic risk of banks.

Keywords: systemic risk; CoVaR; quantile regression method; GARCH model method; DCC-GARCH Pages: 6-28 (search for similar items in EconPapers)
JEL-codes: D81 G00 G32 (search for similar items in EconPapers)
Date: 2021
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