Intraday volatility transmission in global energy markets: A Bayesian nonparametric approach

Martina Danielova Zaharieva, Audronė Virbickaitė and André Portela Santos

Journal of Commodity Markets, 2025, vol. 39, issue C

Abstract: We specify a volatility transmission model for international energy markets that divides a global trading day into three distinct trading zones, allowing us to investigate the heat wave and meteor shower hypotheses proposed in Engle et al. (1990). The resulting multivariate GARCH model is specified using a highly flexible semiparametric Bayesian framework with non-Gaussian innovations, designed to deal with asymmetry and heavy tails found in financial time series. The empirical results for the oil and natural gas futures markets suggest that volatility transmission is a combination of effects that are both related to volatility in the same region and volatility in the region immediately preceding it. Furthermore, accounting for the fat-tailed behavior not only dramatically improves the in-sample fit, but also helps to uncover additional cross-market (or cross-country) effects and gives us further insights into the exact channels through which energy shocks are transmitted throughout the world. Finally, accounting for both heat wave and meteor shower effects within a non-Gaussian framework leads to substantial improvements in the accuracy of Value-at-Risk estimates.

Keywords: COVID-19; Credible intervals; Dirichlet process mixture (DPM); Marginal log likelihood; Volatility spillovers; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C11 C14 C51 C52 C58 G10 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jocoma:v:39:y:2025:i:c:s2405851325000406

DOI: 10.1016/j.jcomm.2025.100496

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