Pricing Weather Derivatives
AbstractThis paper presents a general method for pricing weather derivatives. Specification tests find that a temperature series for Fresno, California follows a mean-reverting Brownian motion process with discrete jumps and ARCH 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.
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Bibliographic InfoPaper provided by Arizona State University, Morrison School of Agribusiness and Resource Management in its series Working Papers with number 28536.
Date of creation: 2004
Date of revision:
derivative; jump-diffusion process; mean-reversion; volatility; weather; Demand and Price Analysis;
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