EconPapers    
Economics at your fingertips  
 

Forecasting volatility of crude oil markets

Sang Hoon Kang, Sang-Mok Kang and Seong-Min Yoon ()

Energy Economics, 2009, vol. 31, issue 1, 119-125

Abstract: This article investigates the efficacy of a volatility model for three crude oil markets -- Brent, Dubai, and West Texas Intermediate (WTI) -- with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices.

Keywords: Persistence; Long; memory; CGARCH; FIGARCH (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (134) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140-9883(08)00153-9
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:31:y:2009:i:1:p:119-125

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 ().

 
Page updated 2019-09-30
Handle: RePEc:eee:eneeco:v:31:y:2009:i:1:p:119-125