Artigo em revista científica Q1
Performance comparison of alternative stochastic volatility models and its determinants in energy futures: COVID‐19 and Russia–Ukraine conflict features
Mário Fernandes (Fernandes, M. C); José Carlos Dias (Dias, J. C.); João Nunes (Nunes, J.);
Título Revista
Journal of Futures Markets
Ano (publicação definitiva)
Estados Unidos da América
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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 (SV) models is estimated using daily prices for our futures contracts between 2005 and 2023. Moreover, to assess the impacts of COVID‐19 and the Russia–Ukraine conflict on volatility, we analyze these two subsamples. Overall, we find that: (i) the Bayes factor shows that the SV model with t‐distributed innovations out performs the competing models; (ii) crude oil contracts with different expiry dates may require the introduction of leverage effects; (iii) the t‐distributed innovations remain the appropriate model for the COVID‐19 subsample, while jumps are needed in the conflict period; and (iv) 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 the agreements for the best models.
Bayesian econometrics,Commodities,Energy markets,Futures contracts,Markov chain Monte Carlo,Stochastic volatility
  • Economia e Gestão - Ciências Sociais
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Referência de financiamento Entidade Financiadora
UIDB/00315/2020 Fundação para a Ciência e a Tecnologia