Measuring systemic risk and dependence structure between real estates and banking sectors in China using a CoVaR‐copula method

The aim of this paper is to study the dependence structure between the real estate and the banking sectors in China. Various time‐varying symmetric and asymmetric copula functions of the elliptical and Archimedean families are used to model the underlying dependence structure. Furthermore, it analyses risk spillover effects between these two sectors by quantifying three risk measures, namely, the value at risk (VaR), the conditional value at risk (CoVaR) and the delta conditional value at risk (ΔCoVaR). Over the period from January 2005 to March 2019, the empirical results show that there exists evidence of significant and symmetric dependence structure between these two sectors and Student's t copulas best capture this dependence. Moreover, we find that there are significant risk spillover effects from the real estate to the banking sectors, and vice versa. By considering different periods of financial distress, the empirical results show that risk spillover effects during the 2015–2016 Chinese stock market turbulence period are much significant than that during the 2007–2008 global financial crisis. Furthermore, the statistical tests show that the real estate sector contributes significantly to systemic risk of the banking sector, and vice versa. Finally, some useful implications are summarized for investors and policymakers.