Pricing Weather Derivatives
提出一种天气衍生品的一般定价方法，基于加州弗雷斯诺的温度序列建立均衡定价模型，并通过蒙特卡洛模拟等方法比较不同定价方式，证明其对加州特色作物种植者的风险管理价值。
This article presents a general method for pricing weather derivatives. Specification tests find that a temperature series for Fresno, CA follows a mean‐reverting Brownian motion process with discrete jumps and autoregressive conditional heteroscedastic errors. Based on this process, we define an equilibrium pricing model for cooling degree day weather options. Comparing option prices estimated with three methods: a traditional burn‐rate approach, a Black‐Scholes‐Merton approximation, and an equilibrium Monte Carlo simulation reveals significant differences. Equilibrium prices are preferred on theoretical grounds, so are used to demonstrate the usefulness of weather derivatives as risk management tools for California specialty crop growers.