Utilizing the information content of trading and non-trading periods including lunch breaks for stock market volatility forecasting

Purpose- This study investigates the empirical effects of information dissemination dynamics across active trading sessions and market closures on Chinese stock market volatility. Methodology- This paper uses intraday data to explore the influences of information transmission during trading and non-trading periods (including lunch breaks that divide each trading day into two distinct sessions) on volatility in China’s stock markets, and to forecast such volatility through modelling. Findings- Its findings demonstrate that absolute overnight return and positive lunch break return both play important roles in future volatility. Moreover, the empirical results suggest that morning-session RRV is positively linked with volatility over longer prediction horizons, and afternoon-session RRV, with volatility over shorter ones. Conclusion- Finally, this paper proposes that a simplified model, which only considers morning-session RRV, can improve the accuracy of prediction of future realized volatility. Keywords: Overnight returns, trading volume, lunch break returns, morning and afternoon sessions, realized range-based volatility.