Author(s)

Jiayi Wang ¹, Yile Wang ²

Affiliation(s)

¹ Digital College, Beijing Technology and Business University, Beijing, China
² School of Economics, Beijing Technology and Business University, Beijing, China

Corresponding Author

Yile Wang

ABSTRACT

Agricultural production is highly vulnerable to market price fluctuations, which may lead to unstable income and increased operational risks for farmers. To improve the rationality of guarantee level selection in agricultural "insurance + futures" risk management, this paper proposes an optimization framework based on the Constant Relative Risk Aversion (CRRA) utility function and stochastic market analysis. First, a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is introduced to characterize the volatility characteristics of agricultural product prices, and a Monte Carlo simulation method is employed to describe possible future market scenarios. Then, an insurance-futures payoff model is established to evaluate farmers' wealth changes under different guarantee levels. By maximizing the expected utility under various risk preference conditions, the optimal guarantee level is determined while considering insurance cost constraints. Experimental results demonstrate that the proposed framework can effectively capture the influence of risk aversion, market volatility, and premium cost on guarantee decisions, providing a quantitative approach for agricultural risk management strategy design. The proposed method offers a decision-making reference for improving the flexibility and efficiency of agricultural insurance-futures products.

KEYWORDS

Agricultural insurance; Insurance + Futures; CRRA utility function; Optimization of coverage levels

CITE THIS PAPER

Jiayi Wang, Yile Wang. Optimal Guarantee Level Optimization for Agricultural Insurance-Futures Based on CRRA Utility Maximization. Agricultural & Forestry Economics and Management (2026). Vol. 9, No. 1, 75-84. DOI: http://dx.doi.org/10.23977/agrfem.2026.090110.

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