Overnight Trading Matters!—Volatility Forecast in the Crude Oil Futures Market

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Authors: Jing Hao, Feng He, Liyuan Qin
Cited by: 0
References: 70

Abstract

ABSTRACT This study primarily explores the potential of night‐time trading information to enhance the prediction accuracy of WTI crude oil futures price volatility within the HAR framework. Out‐of‐sample analysis reveals that integrating daily, monthly, or weekly overnight information into the HAR models notably improves their capacity to forecast crude oil futures price volatility. This suggests that overnight information effectively improves forecasting performance. Moreover, we demonstrate that short‐term overnight information possesses predictive power surpassing that of long‐term information. Finally, these findings are robust to the application of the recursive window method and the HAR‐CJ model.

Fields of Study & Subjects

Financial Risk and Volatility Modeling Market Dynamics and Volatility Stock Market Forecasting Methods

Publication details

Journal / source
Journal of Forecasting
Volume
45
Issue
4
Pages
1511–1528
Publication date
18 January 2026
Language
EN