Systematic Research on Multi-dimensional and Multiple Correlation Contagion Networks of Extreme Risk in China’s Banking Industry

The extreme risks of banks not only cause losses to themselves but also bring external risks to other financial institutions. Current research mainly focuses on the one-way risk spillover of financial institutions and ignores the relevance of banks as financial network nodes. We have constructed multi-dimensional and multiple correlation contagion networks with directed weight to describe the basic network characteristics of banks based on the data collected from 14 banks listed in China from January 1, 2009, to December 31, 2020. The network is weighted with the entropy weight method to establish a network center index to identify systemically important banks. The following conclusions were drawn. Firstly, the MVMQ-CAViaR model can effectively fit two-way, multi-dimensional and multiple correlation contagion when measuring bank extreme risk contagion. The multi-dimensional multiple correlation contagion effects of bank extreme risk were significant. Secondly, the multi-dimensional multiple correlation contagion networks were found to have the characteristics of a small-world network and a scale-free network. According to the relative relationship and direction of spillover absorption, banks can be clustered into four roles: Net absorbers, brokers, two-way spillover, and net spillover. Thirdly, most joint-stock commercial banks have high systemic importance and strong network integration centrality in the extreme risk contagion network. Our research will provide some new ideas for market supervision of financial institutions.