The contribution of shadow banking risk spillover to the commercial banks in China: based on the DCC-BEKK-MVGARCH-Time-Varying CoVaR Model

In recent years, with the rapid expansion of commercial banks' non-standardized business, the systematic correlation between shadow banking and commercial banks in China has been gradually enhanced, which enables the partial liquidity crisis of shadow banking to spread rapidly to commercial banks, leading to the increased vulnerability of China's financial system. Based on this, we built shadow banking indexes of trusts, securities, private lending and investments, introduced the dynamic correlation coefficient calculated by the dynamic conditional correlation multivariate GARCH model into the improved CoVaR model, and used the DCC-BEKK-MVGARCH-Time-Varying CoVaR Model to measure the risk overflow contribution of shadow banking in China. We find that shadow banking and commercial banks have an inherent relationship. Due to their own risks, different types of shadow banking contribute to the risk spillover to commercial banks in different degrees. The risk correlation between shadow banking and commercial banks fluctuates. Securities, trusts, private lending and investments shadow banking have different degrees of risk spillover contributions to commercial banks. Securities shadow banking has the highest risk spillover contribution. The next is trusts shadow banking. The risk spillover contributions from private lending and investments shadow banking are lower, but their volatilities are higher. The supervising department should standardize the information disclosure system of shadow banking and establish the risk firewall of commercial banks and shadow banking from the perspective of the risk spillover contribution.