Forecasting oil price volatility using high-frequency data: New evidence
Yu Wei and
International Review of Economics & Finance, 2020, vol. 66, issue C, 1-12
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)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:66:y:2020:i:c:p:1-12
Access Statistics for this article
International Review of Economics & Finance is currently edited by H. Beladi and C. Chen
More articles in International Review of Economics & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().