Modeling Jump and Continuous Components in the Volatility of Oil Futures
AbstractIn 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.
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Bibliographic InfoArticle provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.
Volume (Year): 13 (2009)
Issue (Month): 3 (May)
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Web page: http://www.degruyter.com
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- Sévi, Benoît, 2014.
"Forecasting the volatility of crude oil futures using intraday data,"
European Journal of Operational Research,
Elsevier, vol. 235(3), pages 643-659.
- Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Working Papers 2014-053, Department of Research, Ipag Business School.
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