Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network

In the post-epidemic period, the international economic structure has been readjusted, with risks contagious across financial and economic systems. This paper primarily uses the high-frequency TENET network and the Granger-causality network to describe the interconnectedness between the tail risk of stock volatility and investor sentiment, then the two-layer network is constructed by the generalized variance decomposition method to examine the inter-layer connectedness. Based on the two-layer network, the heterogeneity frequency response of network connectedness and dynamic network structure are further analyzed from the perspective of frequency domain. The study found that the tail risk of high-frequency stock volatility displays industry heterogeneity and time-varying property, and investor sentiment contagion network provides information transmission medium for stock risk. The double-layer network study found that stock volatility in consumer goods industry exhibits higher risk spillover to investor sentiment. The diversified financial industry, real estate industry and energy industry in the two-layer network are systemically important industries. In addition, the study of the frequency domain dynamic network found that the connectedness volatility in the short-term risk network of stock volatility was significantly higher than that of the investor sentiment network, and the short-term risk spillover effect of the network played a leading role in the total risk spillover. The research conclusions provide reference for preventing systemic risks from the perspective of systemically important industries and cyclical fluctuations. • Use high-frequency TENET network to measure tail risk of stock price volatility. • Describe investor sentiment contagion between industries based on Granger-causality network. • The two-layer network of high-frequency stock price volatility and investor sentiment is constructed. • The risk spillover effect and interconnectedness of two-layer network are measured. • Dynamic network structure based on frequency domain is analyzed for industry risk contagion.