Pricing the Physical Gray Rhino: Extreme Climate Shocks and Long-Run Volatility Dynamics in Soft Commodities

Abstract

Against the backdrop of intensifying global climate variability, extreme weather events are increasingly inflicting physical disruptions on agricultural supply chains; yet traditional financial asset pricing models predominantly neglect these long-term physical constraints. This paper investigates the transmission mechanism of physical climate risks into financial markets by employing a GJR-GARCH-MIDAS (Mixed Data Sampling) framework, utilising daily returns of soft commodity futures—cocoa and coffee—alongside the monthly Oceanic Niño Index (ONI) released by NOAA, over the period January 2000 to June 2026. Empirical results reveal that low-frequency ENSO climate anomalies significantly and positively elevate the long-run secular volatility of tree-based soft commodity futures (θ = 0.233, p < 0.01 for cocoa; θ = 0.105, p < 0.10 for coffee), while exerting no statistically significant effect on annual crop futures such as soybeans (θ = −0.417, p < 0.01 in the opposite direction). This striking heterogeneity is rooted in the divergent biological supply elasticities between perennial tree crops and short-cycle annual crops. Our findings offer a robust empirical foundation for correcting long-run volatility estimates in derivative pricing, and provide forward-looking risk management insights for multinational food corporations and central banks navigating agricultural inflation.

Author abstract from the research manuscript. Typography and line breaks have been normalized; the linked source may show a different manuscript version.