Abstract: In recent years, increasing uncertainty in the global economic and trade environment—driven in particular by agricultural tariff adjustments and bulk commodity price fluctuations resulting from Sino-U.S. trade frictions—has significantly amplified the need for more effective agricultural risk management strategies. This study proposes a new model for predicting implied volatility based on related listed commodities, termed the Associated Enhanced Relative Value (AERV) model. Empirical results show that by integrating data from financial instruments correlated with the target commodity, the AERV model significantly improves the accuracy of implied volatility predictions. This provides more reliable support for option pricing and risk mitigation. Building on this model, we design an automated over-the-counter (OTC) options hedging system capable of guiding and executing Delta hedging operations, effectively enhancing risk diversification and control in the options market. Additionally, this paper explores the integration of the “Insurance + Futures” model into agricultural risk management, highlighting the complementary roles of futures markets and agricultural insurance. The findings indicate that the model plays a vital role in stabilizing farmers’ incomes and mitigating risks associated with price volatility.