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The forecast ability of a belief-based momentum indicator in full-day, daytime, and nighttime volatilities of Chinese oil futures

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  • Li, Yan
  • Huynh, Luu Duc Toan
  • Xu, Yongan
  • Liang, Hao

Abstract

China launched its domestic crude oil futures market in 2018 and this nascent market is steadily developing. Studying volatility predictability for Chinese crude oil futures has important academic and practical significance. In this study, we examine the predictive impacts of a novel predictor, the belief-based momentum indicator of conditional past return (CPR), a cluster of predictors from the domestic (Chinese) stock and oil markets and the US stock and options markets, and global finance-related indicators. In addition to the full-day oil realized volatility (ORV), we also forecast the daytime and nighttime ORVs. First, we find that the novel CPR indicator has significant incremental predictive information for the full-day, daytime, and nighttime ORVs, whether in the short, middle, or long term. Furthermore, the CPR indicator is the most reliable among the four endogenous predictors. Second, predictors of the Chinese stock market have no effective predictive information; instead, predictors from the US stock and options market have great impacts on future Chinese ORVs. Third, our evidence shows that the predictability of the night ORV is half that of the daytime ORV, and the VIX is relevant for the nighttime ORV. Our research helps Chinese policymakers improve the crude oil market mechanism and prevent market risks.

Suggested Citation

  • Li, Yan & Huynh, Luu Duc Toan & Xu, Yongan & Liang, Hao, 2023. "The forecast ability of a belief-based momentum indicator in full-day, daytime, and nighttime volatilities of Chinese oil futures," Energy Economics, Elsevier, vol. 127(PB).
    • Handle: RePEc:eee:eneeco:v:127:y:2023:i:pb:s0140988323005625
    DOI: 10.1016/j.eneco.2023.107064
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    More about this item

    Keywords

    Belief-based momentum; Chinese oil futures market; HAR; Volatility forecasting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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