Abstract
We examine the risk spillovers in the Chinese financial system by adopting a time-varying copula-CoVaR approach. We first identify the systemically important financial institutions for each industry group in China’s financial sector in a dynamic context. We then find strong evidence of upside and downside risk spillovers between these key institutions and the financial system, by quantifying value at risk (VaR), conditional VaR (CoVaR) and delta CoVaR (ΔCoVaR) through time-varying copulas. The empirical results further reveal asymmetric downside and upside risk spillover effects, indicating asymmetric hedging strategies for investors during market upturns and downturns.
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Notes
It should be mentioned that there are several alternative methods when estimating the time-varying parameters of the copula models. On the other hand, the regime switching copulas allow the changes of functional forms of couples over time. A detailed review can be found in Manner and Reznikova (2012). The detailed description of these approaches, however, is beyond the scope of this study.
We thank an anonymous reviewer for this comment.
The empirical analysis is based on the 5% VaR. When using the 1% VaR, our main findings remain robust. For brevity, the results using the 1% VaR are not reported here but can be provided upon request.
The SIFIs identified for each of the three industrial groups using the static copula-CoVaR approach are the same institutions as identified by the time-varying copula CoVaR approach, namely, SPDB, PS and PAI for banks, diversified financials and insurance, respectively. The estimation process is not shown here for brevity.
For brevity, the results of risk spillover and tests of asymmetric effects for diversified financials-PS and insurance-PAI are not reported here.
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Supports from the National Natural Science Foundation of China under Grant Nos. 72022020, 71974159, 71974181 and the 111 Project (Grant No.: B16040) are acknowledged.
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Wu, F., Zhang, Z., Zhang, D. et al. Identifying systemically important financial institutions in China: new evidence from a dynamic copula-CoVaR approach. Ann Oper Res 330, 119–153 (2023). https://doi.org/10.1007/s10479-021-04176-z
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DOI: https://doi.org/10.1007/s10479-021-04176-z