Modeling energy price dynamics: GARCH versus stochastic volatility

被引:132
作者
Chan, Joshua C. C. [1 ]
Grant, Angelia L. [1 ]
机构
[1] Australian Natl Univ, Res Sch Econ, Canberra, ACT, Australia
基金
澳大利亚研究理事会;
关键词
Bayesian model comparison; Crude oil; Natural gas; Moving average; Jumps; Leverage; t distribution; CRUDE-OIL MARKET; INFLATION; FUTURES; SHOCKS; RISK;
D O I
10.1016/j.eneco.2015.12.003
中图分类号
F [经济];
学科分类号
02 ;
摘要
We compare a number of GARCH and stochastic volatility (SV) models using nine series of oil, petroleum product and natural gas prices in a formal Bayesian model comparison exercise. The competing models include the standard models of GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, and t distributed and moving average innovations. We find that: (1) SV models generally compare favorably to their GARCH counterparts; (2) the jump component and t distributed innovations substantially improve the performance of the standard GARCH, but are unimportant for the SV model; (3) the volatility feedback channel seems to be superfluous; (4) the moving average component markedly improves the fit of both GARCH and SV models; and (5) the leverage effect is important for modeling crude oil prices-West Texas Intermediate and Brent-but not for other energy prices. Overall, the SV model with moving average innovations is the best model for all nine series. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:182 / 189
页数:8
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