Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China

摘要

This article uses the stock market regional indexes of 31 provinces (include Province-level municipalities and Minority Autonomous Regions) in mainland China as a sample, and constructs an inter-regional volatility spillover network of China?s stock market based on the GARCH-BEKK model. Through network centrality analysis, Diebold and Yilmaz?s spillover index method and block model analysis, we comprehensively analyze the risk contagion effect among different regions in China?s stock market. The empirical results show that: (i) The risk contagion intensity (risk reception intensity) in various regions of China?s stock market has a typical ?core-periphery? distribution characteristic due to regions? different levels of economic development. (ii) There are obvious risk spillover effect in China?s stock market, among which the economically developed regions along the southeastern coast of China, such as Beijing, Shanghai, Zhejiang and Jiangsu, are the main risk transmitters, while the economically undeveloped regions in the Midwest of China, such as Xinjiang, Xizang, Gansu, Nei Menggu and Qinghai are the main risk receivers. (iii) Each region is divided into 4 blocks according to their respective roles in the risk spillover process in China?s stock market. Block 1 that is composed of the economically underdeveloped regions in the Midwest is the ?main benefit block?, it acts as a ?receiver?. Block 2 that is composed of regions with strong economic growth vitality in the Midwest is a ?Bilateral spillover block?, it both plays the role of ?receiver? and ?transmitter?. Block 3 that is composed of developed regions along the southeast coast, it acts as a ?transmitter?; Block 4 that is composed of the relatively fast-growing regions in the Southwest is the ?brokers block?, it serves as a ?bridge?. The results of this article can provide some reference for investors in financial institutions and decision makers in financial regulators.