Modeling Asymmetric Dependencies in Turkish Agricultural Markets: A Time-Varying Copula Approach

This study investigates the dependence structure between Turkish agricultural commodity prices (barley, corn, grain, and wheat) and key financial variables: global crude oil prices (WTI/USD), the USD/TRY exchange rate, and local crude oil prices (WTI/TRY). The purpose is to evaluate how these relationships evolve over time and to identify the most significant financial drivers of agricultural price dynamics in Turkey. The analysis is based on daily data from August 1, 2019, to January 1, 2025. Using five copula models (Clayton, Frank, Gumbel, Gaussian, and Student’s t) and three correlation measures (Pearson, Spearman, Kendall), the study captures both linear and nonlinear dependencies across different time horizons by aggregating returns from 1 to 45 days. This multi-scale approach enables the assessment of short- and medium-term co-movements and tail dependencies. The findings reveal that dependence strengthens with longer return horizons, highlighting the growing impact of financial variables on commodity prices over time. Among the variables, WTI/TRY exhibits the strongest and most consistent dependence, especially with wheat and grain, reflecting the critical role of local energy costs in agricultural production. WTI/USD shows moderate global-level influence, while USD/TRY demonstrates weaker short-term dependence but becomes relevant in the tails over longer horizons. The t copula proves to be the most suitable model, effectively capturing both upper- and lower-tail dependence. These results have important implications for risk management, agricultural pricing, and policy decisions in energy-dependent economies.