Journal
ENERGY ECONOMICS
Volume 54, Issue -, Pages 182-189Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.eneco.2015.12.003
Keywords
Bayesian model comparison; Crude oil; Natural gas; Moving average; Jumps; Leverage; t distribution
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Funding
- Australian Research Council [DE150100795]
- Australian Research Council [DE150100795] Funding Source: Australian Research Council
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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.
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