This paper studies the volatility dynamics of futures contracts on crude oil, natural gas and gasoline. An appropriate Bayesian model comparison exercise between seven stochastic volatility models is estimated using daily prices for our futures contracts between 2019 and 2022 to examine the COVID-19 and Russia-Ukraine conflict effects. Alternative Bayesian information criteria are also tested. Overall, we find that: (i) the Bayes factor shows that the stochastic volatility model with t-distributed innovations outperforms the competing models for crude oil and gasoline, while incorporating jumps seems more appropriate to model natural gas contracts and to accommodate the impacts of the Russia-Ukraine conflict; (ii) contracts with different expiry dates may require alternative stochastic volatility behaviours and (iii) other Bayesian criteria more appropriate to short-term predictive ability—such as the conditional and the observed-date deviance information criterion—suggest other rank order to model our futures contracts, despite some agreements in the best models.

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