Forecasting volatility of crude oil markets

被引:237
作者
Kang, Sang Hoon [2 ]
Kang, Sang-Mok [1 ]
Yoon, Seong-Min [1 ]
机构
[1] Pusan Natl Univ, Dept Econ, Pusan 609735, South Korea
[2] Gyeongsang Natl Univ, Dept Business Adm, Jinju 660701, South Korea
基金
新加坡国家研究基金会;
关键词
Persistence; Long memory; CGARCH; FIGARCH; LONG-RANGE DEPENDENCE; PRICE SHOCKS; TIME-SERIES; MEMORY; RISK; ASYMMETRY; VARIANCE; IMPACT;
D O I
10.1016/j.eneco.2008.09.006
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:119 / 125
页数:7
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