Episodes of extreme volatility have become a defining feature of globalenergy and commodity markets, with crises such as the COVID-19 pandemic, and the Russia–Ukraine conflict exposing systemic vulnerabilities and accelerating risk transmission across asset classes. This review systematically synthesizes empirical research on volatility modeling in energy and commodity markets between 2015 and 2025, under crisis conditions. Using a structured review protocol across Scopus and Web of Science databases, we identify 52 studies employing diverse econometric approaches, ranging from GARCH and VAR models, copulas, wavelets, and machine-learning methods. Our synthesis reveals three critical patterns. First, a structural shift from episodic to persistent volatility has occurred in the post-2020 “polycrisis” era, where overlapping shocks compound instability: spillover increased by 60-80% during the 2008 crisis, approximately doubled during COVID-19, and rose by an additional 12-14% following the Russia-Ukraine conflict. Second, volatility transmission operates simultaneously through fundamental, financial, sentiment, geopolitical, and climate channels, each with distinct temporal signatures and interactions. Third, apparent contradictions in the literature often dissolve when analyzed across multiple dimensions of time, frequency, and regime, underscoring the need for layered methodological approaches. We argue that while significant advances have been made in capturing crisis-driven volatility, substantial gaps remain, particularly in the treatment of energy-transition metals (ETMs) that have an average return and volatility connectedness of 45%. The review highlights that future research must expand empirical coverage beyond oil-centered analysis, integrate omitted critical minerals, and adopt multi-method frameworks capable of addressing compound shocks. Policy implications include the need for coordinated strategies to strengthen supply-chain resilience, regulate speculative excess, anchor market sentiment, manage geopolitical risks, and confront climate-related uncertainties. • Reviews volatility and spillover dynamics in energy and commodity markets during crises. • Identifies oil as both a primary source and receiver of systemic risk across asset classes. • Critically evaluates GARCH, VAR, spillover indices, and network-based modeling methods. • Shows that concurrent shocks and financialization intensify volatility and cross-market contagion. • Highlights research gaps in modeling layered crises and distinguishing structural from crisis-driven volatility.
Al-Haddad et al. (Fri,) studied this question.
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