Pricing Weather Derivatives

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.