Regime-dependent volatility spillover asymmetry in Shanghai and Hong Kong stock markets with forecasting and portfolio inferences

Abstract

This study examines asymmetric volatility spillovers between Shanghai and Hong Kong equity markets using a novel regime-dependent spillover index within a Markov-switching VAR framework. High-frequency data analysis reveals: (1) Post-2014 Stock Connect amplifies spillovers with pronounced asymmetry, particularly adverse shock dominance during turbulence, establishing Shanghai as the primary negative volatility transmitter; (2) While regime-switching asymmetric models enhance forecasting accuracy, portfolio strategies under conventional BEKK and aBEKK models are constrained by post-Program integration. Our regime-dependent (RD) model significantly improves portfolio efficiency while reducing rebalancing costs. Crucially, by leveraging regimes of realized volatility derived from intraday 5-min data, the RD approach provides policymakers and investors with superior tools for mitigating cross-market risk transmission during financial liberalization. Findings demonstrate that accounting for regime shifts and asymmetry is essential for improvement of volatility forecast and effective risk management in emerging markets.