Modeling jump and continuous components in the volatility of oil futures

Tseng Chan Tseng*, Hui-min Chung, Chin Sheng Huang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


In this study, we use the 'heterogeneous autoregressive' (HAR) model and replace all squared returns with a squared range to estimate realized range-based volatility (RRV) forecasts for oil futures prices. Our findings demonstrate that the HAR-RRV models, involving volatility measures with a realized range-based estimator, successfully capture the long-term memory behavior of volatility in oil futures contracts. We find that realized range-based bi-power variation (RBV), which is also immune to jumps, is a better regressor for future volatility prediction, significantly outperforming the AR model. Similar to the findings for financial markets, we also find that the jump components of RRV have little predictive power for oil futures contracts.

Original languageEnglish
Article number5
JournalStudies in Nonlinear Dynamics and Econometrics
Issue number3
StatePublished - 13 May 2009


  • HAR-RRV model
  • High-frequency data
  • Oil futures
  • Realized range-based variance
  • Volatility forecasting

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