Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach
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Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach Fenghua Wen1,2 · Kaiyan Weng1 · Wei‑Xing Zhou3 Accepted: 12 October 2020 © Springer Nature Limited 2020
Abstract This study proposes an extension of the Asymmetric CoVaR method in Espinosa et al. (J Bank Finance 58: 471–485, 2015) to capture the time-varying asymmetric responses of the financial system to positive and negative shocks to individual institutions. Building on the extended method and considering a set of Chinese financial institutions, we assess the extent to which distress within different institutions contribute to systemic risk. To provide a formal ranking of risk contributions, we implement the significance and dominance tests with bootstrap Kolmogorov–Smirnov statistics. The estimates of the extended Asymmetric CoVaR method reveal an asymmetric pattern that characterizes the tail interdependence in the Chinese financial system and this pattern changes dynamically over time. Particularly, the impact on the system of a fall in individual market value is only slightly larger than that of an increase during tranquil years. However, the entire system becomes extremely sensitive to downside losses than to upside gains during crises. The result also raises concern about privately owned banks in that they are systemically riskier than stateowned banks and other institutions. Using panel regressions, we also find firm characteristics such as institution size and volatility are important predictors of systemic risk contribution. Keywords Systemic risk · Tail-risk dependence · Asymmetric CoVaR · Timevarying
* Wei‑Xing Zhou [email protected] 1
School of Business, Central South University, Changsha 410083, Hunan, China
2
Supply Chain and Logistics Optimization Research Centre, Faculty of Engineering, University of Windsor, Windsor, ON, Canada
3
Department of Finance, Department of Mathematics and Research Center for Econophysics, East China University of Science and Technology, Shanghai 200237, China
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F. Wen et al.
Introduction The global financial crisis of 2008 began in the United States and took on worldwide proportions shortly after the collapse of Lehman Brothers, eventually affecting both developed and emerging markets. More recently, the escalation of the 2020 COVID pandemic further shows the fragility of the world we live and how vulnerable we are as a society to exceptional risks. The sudden and simultaneous economic turn-downs in many countries triggered important questions about the accurate modeling of tail interdependence and the timely measurement of systemic risks. A fast-growing research and regulatory interest is thus directed towards this subject, originating diverse models and measures that emphasize different aspects of systemic risks, such as the connectedness network of Diebold and Yılmaz (2014), the marginal expected shortfall of Brownlees and Engle (2016), the conditional value-at-risk of Adrian and Brunnermeier (2016), the systemic ex
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