Spillover risks between agricultural commodities (2015- 2025) : emergence of new risk drivers

Abstract

ABSTRACT: This study assesses the dynamics of volatility and risk transmission among US agricultural commodity futures markets from 2015 to 2025, emphasizing the effects of exogenous shocks: the US-China trade war (2018-2019 and escalation in 2025), the COVID-19 pandemic (2020-2021), and the Russia-Ukraine conflict (2022-2023). The central research question investigates whether tariffs, geopolitical shocks, and health shocks alter conditional volatility and systemic risk transmission in commodity returns. Weekly returns of the Bloomberg Commodity Index (BCOM) and its agricultural sub-indices (grains, livestock, agricultural products) and disaggregated contracts (corn, soybeans, live cattle, lean hogs) were studied using a multivariate DCC-GARCH model with marginal eGARCH(1,1) and Student's t-residues to capture skewness, persistence, leptokurtosis, and dynamic correlations. Systemic and marginal risks are quantified using Conditional Value at Risk (CoVaR) and DeltaCoVaR, adjusted with Cornish-Fisher expansion for nonnormality. Empirical findings validate the hypothesis. So, shocks induce regime shifts in correlations and increase tail risks. Volatility persistence is ! > 0.8, with negative shocks amplifying variance, in other words, a positive leverage effect. Grains and soybeans exhibit contagion effects, with DeltaCoVaR peaks during the Russia-Ukraine war at 0.0436 and during COVID-19 at ?0.0403. Bootstrap confidence intervals validate statistical significance. The results indicate intensified interconnectedness across commodities, particularly during the U.S.-China trade war and the COVID-19 pandemic. These findings suggest that external shocks are associated with higher systemic risk within agricultural futures markets.