Futures-based forecasts: How useful are they for oil price volatility forecasting?
Stavros Degiannakis () and
George Filis ()
Energy Economics, 2019, vol. 81, issue C, 639-649
Oil price volatility forecasts have recently attracted the attention of many studies in the energy finance field. The literature mainly concentrates its attention on the use of daily data, using GARCH-type models. It is only recently that efforts to use more informative intra-day data to forecast oil price realized volatility have been made. Despite all these previous efforts, no study has examined the usefulness of futures-based models for oil price realized volatility forecasting, although the use of such models is extensive for oil price predictions. This study fills this void and shows that futures-based forecasts based on intra-day data provide informative forecasts for horizons that span between 1-day and 66-days ahead. More importantly, these results hold true even during turbulent times for the oil market, such as the Global Financial Crisis of 2007–09 and the oil collapse period of 2014–15.
Keywords: Brent crude oil; Realized volatility; Forecasting; Futures-based forecasts (search for similar items in EconPapers)
JEL-codes: C22 C53 G13 Q47 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: Futures-based forecasts: How useful are they for oil price volatility forecasting? (2019)
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:eneeco:v:81:y:2019:i:c:p:639-649
Access Statistics for this article
Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant
More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().