Purpose This paper examines the volatility spillover effects across four key commodities (gas, WTI, wheat, gold), bitcoin and G7 stocks during crisis periods, including the COVID-19 pandemic and the Ukraine war. The objective is to comprehend how linkages vary under extreme conditions to inform risk management and portfolio strategies. Design/methodology/approach The study applies a multi-method approach: time-varying parameter, quantile vector autoregression and time–frequency connectedness. It permits exploring directional connectedness and regime-specific behaviours across quantiles and frequency domains by using daily indices from January 2017 to February 2025. Findings The results reveal time-varying connectivity that intensifies during crises. WTI shifts from net receiver to significant transmitter of shocks in war, highlighting the energy market's vulnerability to conflict. The S&P 500 became a net recipient during the war. Commodities show no significant interconnection. Gold and Bitcoin act similarly, receiving shocks particularly during the pandemic. The Nikkei's behaviour aligns with Bitcoin and commodities. G7 indices, except Nikkei, are risk amplifiers while Bitcoin and commodities (except WTI) are consistent receivers. Extreme quantiles indicate symmetric net transmission. Short-term spillovers dominate, implying faster propagation of shocks, long-term connectedness is weak and less persistent. Practical implications Findings highlight the necessity for dynamically adjusting portfolio strategies in response to crises. Short-term volatility dominance implies the need for tactical allocation. Shock propagators can't play anything in portfolio strategies, while consistent receivers are suitable candidates as safe-haven assets and hedging instruments. WTI must be monitored to rebalance risk. Commodities can be used to diversify within the commodity sector. Originality/value This paper combines QVAR and time–frequency analysis to assess the behaviour of conventional and modern financial assets under crises periods. It contributes to the literature by identifying specific roles of each asset across different quantiles and time horizons, enhancing understanding of systemic risk and resilience under stress and offering insights for investment decision-making during disruptions.
Olfa El Aoun (Wed,) studied this question.
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