Hedging downside risk in agricultural commodities: A novel nonparametric kernel method

Qi Jiang and Yawen Fan

Finance Research Letters, 2024, vol. 70, issue C

Abstract: Using a nonparametric kernel method, this paper develops a weighted conditional value-at-risk hedge model to hedge downside risks in agricultural commodities. The model exhibits convexity, ensuring the acquisition of its global optimal solution. Simulations show that the nonparametric kernel method enhances the accuracy of the weighted conditional value-at-risk and hedge ratio determination, outperforming traditional estimation methods. Using major agricultural commodities, empirical evidence shows the superiority of the proposed model in reducing downside risks, compared to the minimum variance, minimum value-at-risk, and minimum conditional value-at-risk hedge models.

Keywords: Downside risk; Weighted conditional value-at-risk; Nonparametric kernel method; Agricultural commodity (search for similar items in EconPapers)
JEL-codes: G11 G14 G15 G23 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:70:y:2024:i:c:s1544612324013692

DOI: 10.1016/j.frl.2024.106340

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