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Forecasting the volatility of crude oil futures using high-frequency data: further evidence

Author

Listed:
  • Feng Ma

    (Southwest Jiaotong University)

  • Yu Wei

    (Southwest Jiaotong University
    Yunnan University of Finance and Economics)

  • Wang Chen

    (Yangtze Normal University)

  • Feng He

    (Nankai University)

Abstract

We forecast the realized volatility of crude oil futures market using the heterogeneous autoregressive model for realized volatility and its various extensions. Out-of-sample findings indicate that the inclusion of jumps does not improve the forecasting accuracy of the volatility models, whereas the “leverage effect” pertaining to the difference between positive and negative realized semi-variances can significantly improve the forecasting accuracy in predicting the short- and medium-term volatility. However, the signed jump variations and its decomposition couldn’t significantly enhance the models’ forecasting accuracy on the long-term volatility.

Suggested Citation

  • Feng Ma & Yu Wei & Wang Chen & Feng He, 2018. "Forecasting the volatility of crude oil futures using high-frequency data: further evidence," Empirical Economics, Springer, vol. 55(2), pages 653-678, September.
    • Handle: RePEc:spr:empeco:v:55:y:2018:i:2:d:10.1007_s00181-017-1294-6
    DOI: 10.1007/s00181-017-1294-6
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