Dynamic and asymmetric spillovers between crude oil, biofuels and agricultural commodities: Evidence from periods of geopolitical tensions and energy policy uncertainty

This study investigates dynamic spillovers in returns and volatility among the ethanol, crude oil (WTI), and corn markets using the Quantile Vector Autoregressive Dynamic Conditional Correlation GARCH (QVAR-DCC-GARCH) model. The model captures time-dependent, nonlinear, and quantile-dependent asymmetric relationships among commodity markets, offering a clearer understanding of the dynamics of market co-movements. The results reveal that spillover effects are dynamic over time and quantile-dependent, with minimal transmission observed in lower quantiles and significantly stronger spillovers during periods of market stress in the upper quantiles. The QVAR identifies significant spillovers where lagged ethanol returns exhibit statistically significant associations with both WTI and corn returns, with spillovers intensifying after mid-2019, coinciding with periods characterized by energy policy shifts and elevated geopolitical tensions. The persistence analysis indicates that while all markets exhibit persistence in volatility, extreme shocks dissipate faster than those around the median. The DCC analysis reveals substantial time-variation in volatility co-movements, particularly for the WTI-Ethanol and Corn-WTI pairs, reflecting the shifting interdependence of energy and agricultural commodity volatilities. These findings emphasize the importance of accounting for non-linear, time-varying dependencies in risk management and policy frameworks, especially as the co-movement and interdependence between energy and agricultural markets strengthen during periods associated with heightened uncertainty, geopolitical stress, and policy regime changes.