What the Night Tells the Day: Forecasting Realized Volatility in Chinese Commodity Markets

This study examines the role of after‐hours information in forecasting Chinese commodity futures volatility, exploiting the introduction of a night session that potentially facilitates real‐time responses to information originating in overseas markets. We generate timely forecasts on future daytime realized volatility for 10 commodity futures, using heterogeneous autoregressive (HAR) models augmented with and without past nights' realized variance measures. Our results reveal significant predictive power, both in‐sample and out‐of‐sample, associated with the night‐time realized volatility across markets. In contrast, the inclusion of daily squared overnight returns as an alternative measure provides limited improvements. Furthermore, we document the empirical merit of separately considering the jump and continuous components in the night‐session price variation, with its superior performance being most pronounced over long forecasting horizons. The improved statistical accuracy is also shown to be economically meaningful for a risk‐averse investor and remains robust to changes in the identification, estimation, and forecasting procedure.