The dependency measures of commercial bank risks: Using an optimal copula selection method based on non-parametric kernel density

Chenglu Jin, Rongda Chen, Diandian Cheng, Sitian Mo and Ke Yang

Finance Research Letters, 2020, vol. 37, issue C

Abstract: This paper focuses on constructing a theoretical overview of using optimal Copula selection method based on non-parametric kernel density for the dependency between each pair of the three main risks: credit risk, market risk and operational risk. Empirically, by using data of 12 listed commercial banks in China, a significant tail dependency between credit risk and market risk is found, while those between operational risk and credit risk or market risk are not obvious. Our finding highlights the importance of investigating operational risks separately in an Internet financial environment.

Keywords: Commercial bank risks; Optimal copula selection method; Non-parametric kernel density; Tail dependency (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:37:y:2020:i:c:s1544612320305365

DOI: 10.1016/j.frl.2020.101706

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