Dynamic correlation and volatility spillover between the stock markets of Shenzhen and Hong Kong

Abstract. Considering the two-way spillovers of market information, this study estab-lishes multivariate Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) models to study the impact of Shenzhen-Hong Kong Stock Connect (SHSC) on the complex co-movement relationship between the stock markets of Shenzhen and Hong Kong in terms of dynamic correlation and volatility spillover. A t-copula Dynamic Conditional Correlation-GARCH (DCC-GARCH) model that combines the copula function with the DCC-GARCH model is established to model the return rate series of stock index at different stages and the characteristic that the dynamic correlation coeffcient changes with time is analyzed emphatically. Moreover, a Baba, Engle, Kraft, Kroner-GARCH (BEKK-GARCH) model is established to measure the changes in the volatility spillover effect between the stock markets in Shenzhen and Hong Kong. The results show that the opening of SHSC has gradually increased the dynamic correlation coeffcient of the two stock markets, and the openness degree of the two stock markets has increased. At the same time, the volatility spillovers of stock markets in Shenzhen and Hong Kong have shifted from one-way spillover to two-way spillovers, indicating that the SHSC mechanism has strengthened the correlation degree and improved the ability of risk spillover in the two stock markets.