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Forecasting the oil futures price volatility: Large jumps and small jumps

Author

Listed:
  • Liu, Jing
  • Ma, Feng
  • Yang, Ke
  • Zhang, Yaojie
Abstract
Macro news drives jumps, however, a jump does not seem to improve the predictability of the simple heterogeneous autoregressive realized volatility model (HAR-RV) in the oil futures market. This paper provides a new insight and seeks to investigate whether truncated jumps can help improve the forecasting ability compared to that achieved using the HAR-RV model and its various extensions with jumps. Our results provide strong evidence that the models incorporating both large and small jumps gain a significantly superior forecasting ability. Specifically, including small jumps in a high-frequency model significantly improves the forecast accuracy at the 1-day forecasting horizon, while including both large and small jumps can achieve a higher forecast accuracy at the weekly and monthly horizons. These findings reveal that considering the decomposed jumps with a certain threshold can increase the forecast accuracy of the corresponding model.

Suggested Citation

  • Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
    • Handle: RePEc:eee:eneeco:v:72:y:2018:i:c:p:321-330
    DOI: 10.1016/j.eneco.2018.04.023
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    More about this item

    Keywords

    Volatility forecasting; oil futures price; Large and small jumps; Predictive evaluation;
    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
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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

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