When prices spike: Identifying excessive volatility in fertilizer markets
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Elsevier
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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.
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fertilizers, prices, price volatility, markets, dynamic programming, modelling, monitoring