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United States Oil Fund volatility prediction: the roles of leverage effect and jumps

Author

Listed:
  • Chao Liang

    (Southwest Jiaotong University)

  • Yin Liao

    (Macquarie University)

  • Feng Ma

    (Southwest Jiaotong University)

  • Bo Zhu

    (Southwest Jiaotong University)

Abstract

We investigate United States Oil Fund volatility predictions using a mixed data sampling modeling framework. There are several vital findings. First, our in-sample analysis shows that both the leverage effect and intraday jumps have a significant impact on the United States Oil Fund realized volatility. Second, our out-of-sample analyses suggest that incorporating the leverage effect can largely improve the United States Oil Fund realized volatility forecasts. Third, using a portfolio exercise, we show that the improved realized volatility forecasts lead to significantly increased economic values. Our results are confirmed by a wide range of robustness checks.

Suggested Citation

  • Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    • Handle: RePEc:spr:empeco:v:62:y:2022:i:5:d:10.1007_s00181-021-02093-5
    DOI: 10.1007/s00181-021-02093-5
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    Cited by:

    1. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    2. Zhang, Li & Li, Yan & Yu, Sixin & Wang, Lu, 2023. "Risk transmission of El Niño-induced climate change to regional Green Economy Index," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 860-872.
    3. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    4. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
    5. Feng, Haoyuan & Liu, Yue & Wu, Jie & Guo, Kun, 2023. "Financial market spillovers and macroeconomic shocks: Evidence from China," Research in International Business and Finance, Elsevier, vol. 65(C).

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    More about this item

    Keywords

    Crude oil fund; Realized volatility; Leverage effect; Jumps; Economic significance;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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