Progress 12/15/02 to 12/14/03
Outputs
Summary of Weather Derivatives: Managing Risk with Market-Based Instruments Weather derivatives may be effective yield-risk management tools for specialty crop growers. Weather derivatives are contingent securities (put or call options, or swaps) that acquire value when the temperature is either greater than or less than some benchmark value, typically 65oF, at some reference location. Before they can become widely traded, however, an accurate, useable pricing model is required. With such a model, buyers and sellers will be able to agree on a mutually beneficial price at which they can exchange risks. Thus, the objectives of this research are to: (1) determine the nature of the process underlying a temperature index for Central California, (2) develop a pricing model for weather derivatives based on this index, (3) evaluate its effectiveness as a revenue risk management tool for a set of representative fruit growers in the Central Valley of California, and (4) provide
computer-based simulation models that growers may use to help evaluate their own use of weather derivatives. The research consists of three stages: (1) develop alternative models for stochastic processes underlying likely weather indices, (2) develop an equilibrium pricing model, and (3) apply the derivative pricing model to case studies involving five different specialty crops in the vicinity of Fresno, CA in order to test their effectiveness as risk management tools. The weather data for this study consist of 30 years of daily average temperatures for Fresno, CA as provided by the U.S. National Climatic Data Center (NCDC). We consider four alternative specifications for the weather process and test among them using a series of likelihood ratio tests. The preferred model is a mean-reverting Brownian motion process with first-order autoregressive errors and a log-normally distributed jump term. This process is considerably more complex than the geometric Brownian motion that is
typically used to model other processes on which financial derivatives are based. Derivative prices are found using a Lucas-type general equilibrium approach because traditional arbitrage-free methods cannot be used. The equilibrium simulation finds that misspecifying the underlying weather process can result in significant overpricing of derivatives based on a cumulative CDD index. Further, we show that the risk premium can be a significant part of the derivative price. Estimates of a simple hedging-effectiveness model also show that more active trading in these derivatives can also be justified in terms of the consistent statistical relationship between variations in temperature and yield. To explore this question further, stochastic simulations of actual farm financial results show that simple long-put, long-call and long-straddle option strategies can indeed be effective in increasing expected net income, improving the risk-return tradeoff as measured by the Sharpe ratio, raising
the Value-at-Risk of a representative grower and increasing the certainty equivalent value of random net income relative to an unhedged benchmark.
Impacts
This research is expected to form the core piece of background knowledge required to develop, implement and proliferate a system of weather derivative trading among specialty crop producers and non-farmers with natural, off-setting weather risks.
Publications
- Richards, T. J., M. Manfredo and D. Sanders. "Pricing Weather Derivates Under Alternative Processes." Amer. J. Agr. Econ. 2003.(in 2nd round review).
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