Forecasting Crude Oil Volatility With Geopolitical Risk: The RSV–MIDAS–GPR Model and Its Economic Value
Year: 2026
Type: article
Abstract: ABSTRACT The paper proposes a new integrated realized stochastic volatility–mixed data sampling–geopolitical risk (RSV–MIDAS–GPR) model to model and forecast crude oil futures volatility. The model jointly models returns and the realized measure of volatility, leverages contemporaneous volatility information, and captures the effects of GPR on crude oil futures volatility. The empirical results demonstrate a significant positive correlation between GPR and crude oil futures volatility. Meanwhile, the RSV–MIDAS–GPR model, which incorporates both GPR and realized volatility, exhibits a synergistic effect, leading to a substantial improvement in out‐of‐sample forecasting performance. Furthermore, the model demonstrates notable capability in identifying high‐volatility states and achieves higher forecasting accuracy than competing models during market turmoil. Finally, economic value tests confirm that the inclusion of GPR provides valuable guidance for investor decision‐making. These findings offer both methodological and empirical contributions to the related research field.
Source: Journal of Futures Markets
DOI: 10.1002/fut.70084
Authors: Ke Yang, Xuebao Yin, Fengping Tian
Institutions: South China University of Technology, Sun Yat-sen University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W7127937545