When prices spike: Identifying excessive volatility in fertilizer markets

Sharp and volatile fertilizer price movements can hinder adoption and reduce agricultural productivity, especially among vulnerable smallholders. Using a nonparametric location-scale approach to model price returns, we quantify the conditional value-at-risk (CVaR) — the high return threshold exceeded with low probability — to identify excessive price spikes in potash, urea, and di-ammonium phosphate (DAP) markets. We use the bias-corrected estimator from Martins-Filho et al. (2018) and propose a simpler estimator based on Hill (1975). Backtesting results indicate superior performance of the Hill-based estimator, supporting its value as a convenient method for detecting unusual fertilizer price surges amid recurring global volatility. • Sharp fertilizer price hikes reduce adoption and farm productivity. • We model price returns using a nonparametric location-scale approach. • We use alternative estimators to detect extreme fertilizer price surges. • The Hill-based method best captures excessive fertilizer price volatility. • Method offers a promising tool for timely price monitoring amid global volatility.