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The Role of Lead-lag Effect in Predicting Crude Oil Futures Volatility: Empirical Evidence from China

Author

Listed:
  • Mengxi He

    (Nanjing University of Science and Technology, School of Economics and Management)

  • Daxiang Jin

    (Southwest Jiaotong University, School of Economics and Management)

  • Yaojie Zhang

    (Nanjing University of Science and Technology, School of Economics and Management)

Abstract

This paper explores the lead-lag effect between volatilities in Chinese crude oil futures and its product futures from the standpoint of raw materials and products. The results of the news-diffusion model show that Chinese crude oil futures react with a delay to product futures. Using the heterogeneous autoregressive realized volatility model and its extensions, our analysis reveals that product futures volatilities can predict the volatility of Chinese crude oil futures. Under the asset allocation exercise, we document that the information from the product futures market can provide investors with a maximum increase of up to 257 basis points in the certainty equivalent return. Finally, the combination approaches and diffusion index methods can further improve predictability and provide investors with more stable economic gains. Our results highlight the critical role of product futures volatility in forecasting crude oil futures volatility, offering novel predictive variables. The conclusions of this paper can help investors and policymakers to better understand the risks of the crude oil futures market, and better manage and prevent risks.

Suggested Citation

  • Mengxi He & Daxiang Jin & Yaojie Zhang, 2026. "The Role of Lead-lag Effect in Predicting Crude Oil Futures Volatility: Empirical Evidence from China," Computational Economics, Springer;Society for Computational Economics, vol. 67(6), pages 5115-5137, June.
    • Handle: RePEc:kap:compec:v:67:y:2026:i:6:d:10.1007_s10614-025-11041-9
    DOI: 10.1007/s10614-025-11041-9
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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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