UTILIZING THE INFORMATION CONTENT OF TRADING AND NON-TRADING PERIODS INCLUDING LUNCH BREAKS FOR STOCK MARKET VOLATILITY FORECASTING
Abstract
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
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Details
| Primary Language | English |
|---|---|
| Subjects | Finance, Finance and Investment (Other), Business Administration |
| Journal Section | Articles |
| Authors | |
| Publication Date | July 30, 2025 |
| Submission Date | February 1, 2025 |
| Acceptance Date | May 4, 2025 |
| Published in Issue | Year 2025 Volume: 12 Issue: 1 |
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