The asymmetric volatility spillover across Shanghai, Hong Kong and the U.S. stock markets: A regime weighted measure and its forecast inference

Based upon generalized spillover index method under Markov switching vector auto-regression (MS-VAR) framework, this paper aims at a regime dependent measure of the volatility spillover asymmetry across Shanghai, Hong Kong and the U.S. stock markets. For that, we apply a regime weighted measure of spillover and its asymmetry. The empirical results show that there existed evident negative asymmetric effect of spillover across the three markets, and it was regime dependent and time-varying: it got intensified under high volatility regime and turned out stronger after the Program of Shanghai-Hong Kong stock connect. The regime weighted measure of spillover asymmetry is found to be reliable; it could be explained appropriately with the economic policy uncertainty and investors' fear in the U.S., extreme shocks like crash of Shanghai stock market and COVID-19 as well as the capital flow through the Program. From in-sample evidence and out-of-sample forecast of Shanghai stock market, we infer that traditional forecast models could be improved if regime dependent spillover and its asymmetry are considered as additional factors.