Forecasting oil price volatility using high-frequency data: New evidence

Wang Chen, Feng Ma, Yu Wei and Jing Liu

International Review of Economics & Finance, 2020, vol. 66, issue C, 1-12

Abstract: In this article, we account for the conditional time-varying volatility of realized volatility to model and forecast oil futures price volatility based on the HAR-RV model and its various extensions. Our empirical results reveal several noteworthy observations. First, the in-sample results indicate that the residuals of the HAR-RV-type models exhibit a significant ARCH effect. Second, the out-of-sample results demonstrate that compared to the linear HAR-RV-type models, the HAR-RV-type models, including the FIGARCH structure models, can generally generate a higher forecast accuracy when forecasting short-term horizon volatility. Third, when predicting middle-term and long-term volatilities, the proposed model, i.e., HAR-S-RV-J-FIGARCH, can exhibit a higher predictive ability.

Keywords: Volatility forecasting; Oil futures price; Volatility of realized volatility; Forecasting evaluation (search for similar items in EconPapers)
JEL-codes: C22 C52 C55 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (38)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:66:y:2020:i:c:p:1-12

DOI: 10.1016/j.iref.2019.10.014

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