Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions

Abstract

We propose multilayer information spillover networks, including return spillover layer, volatility spillover layer, and extreme risk spillover layer in the variance decomposition framework for comprehensively investigating the information spillovers and connectedness among 30 Chinese financial institutions (i.e., banks, securities, and insurers) during the period 2011–2018. We analyze the topological characteristics of static and dynamic multilayer networks at the system and institution levels. We find that (i) at a system level, each layer exhibits a unique network structure and spillover evolution behavior, and multilayer information spillover networks provide synthetic information on the connectedness among financial institutions, and (ii) at an individual level, institutions from different financial sectors play different roles in receiving or sending shocks based on different information spillover or contagion channels. Our findings supply valuable knowledge for investors when they assess risk and optimize asset allocation, and for regulators when they measure connectedness and prevent system risk.