Modeling energy price dynamics: GARCH versus stochastic volatility

Joshua Chan and Angelia Grant

CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University

Abstract: 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 and more flexible models with jumps, volatility in mean and moving average innovations. We find that: (1) SV models generally compare favorably to their GARCH counterparts; (2) the jump component substantially improves the performance of the standard GARCH, but is unimportant for the SV model; (3) the volatility feedback channel seems to be superfluous; and (4) the moving average component markedly improves the fit of both GARCH and SV models. Overall, the SV model with moving average innovations is the best model for all nine series.

Keywords: Bayesian model comparison; crude oil; natural gas; moving average; jumps (search for similar items in EconPapers)
JEL-codes: C11 C52 Q41 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2015-06
New Economics Papers: this item is included in nep-ene, nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Journal Article: Modeling energy price dynamics: GARCH versus stochastic volatility (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2015-20

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