Geopolitical Shocks and Crude Oil Market Tail Risk: Evidence from the Russia–Ukraine Conflict

This study examines the impact of the Russia–Ukraine war on crude oil tail risk using the Conditional Autoregressive Value at Risk (CAViaR) framework. We analyzed 2364 daily observations of West Texas Intermediate (WTI) crude oil futures spanning 1 January 2015 to 11 December 2023, thereby capturing both the pre-war period and the conflict regime. To operationalize the geopolitical shock, we identify four theoretically grounded event dates (21 February, 24 February, 11 May, and 15 June 2022) associated with military escalation and energy-supply disruptions, and incorporate them as exogenous dummy variables. Methodologically, we implement a two-step approach. First, we estimate 1-day Value at Risk (VaR) at the 5% and 1% levels using four alternative CAViaR specifications (Adaptive, Symmetric, Asymmetric, and Indirect GARCH(1,1)) within a rolling-window framework to capture the dynamic evolution of tail risk. Second, we regress the resulting VaR series on geopolitical-event indicators to quantify the marginal effect of war-related developments on downside risk. The empirical results show tail risk increases in oil-market after the most important geopolitical events in all the model specifications across the market characteristics. The Indirect GARCH(1,1) CAViaR model exhibited the highest sensitivity, producing event coefficients of 0.795 (5% VaR) and 0.710 (1% VaR), both significant at the 1% level. Our adaptive specification has magnitudes that are even higher at the extreme tail (2.002 at 1% VaR), further supporting increased vulnerability during periods of escalation in conflict. Evidence from the asymmetric model would also indicate stronger market response to unfavorable news, in line with loss-sensitive investor behavior. In sum, the outcomes indicate that the Russia–Ukraine war considerably elevated the downside risk of crude oil markets and that geopolitical events have economically and statistically significant effects on the tail dynamics. Incorporating event-based geopolitical indicators in the framework of CAViaR, contributes to the literature in energy-market risk modeling and applies practical information to investors, risk managers, and policymakers operating under a dynamic environment characterized by geopolitical uncertainty.