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Modeling energy price dynamics: GARCH versus stochastic volatility

Modeling energy price dynamics: GARCH versus stochastic volatility

Joshua Chan and Angelia Grant

We compare a number of GARCH and stochastic volatility (SV) models using nine series of oil, petroleumproduct 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 tdistributed 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.

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Updated:   18 February 2017 / Responsible Officer:  Dean, Business & Economics / Page Contact:  College Web Team