Downside Risk and Agriculture Commodity Futures Returns: A Study Using Self‐Organizing Maps

This study analyzes downside risk and nonlinear dependence in agricultural commodity futures using a hybrid framework that integrates Self‐Organizing Maps (SOMs) with Copula‐based dependence modeling. Agricultural returns exhibit asymmetric behavior, making linear correlation inadequate for risk assessment. The SOM identifies distinct market regimes based on return dynamics and volatility structure, while Student‐ t and Clayton copulas quantify symmetric and lower‐tail dependence within each regime. Results show a clear escalation of dependence from tranquil to crisis states, with tail‐dependence coefficients rising monotonically across SOM clusters. The Student‐ t copula captures symmetric co‐movements in extreme returns, whereas the Clayton copula highlights strong joint downside risk during high‐volatility phases. These patterns confirm that diversification benefits across agricultural commodities weaken substantially under stress. The proposed SOM–Copula hybrid framework provides a regime‐sensitive approach to modeling tail interdependence in commodity markets.