Weather Derivatives: Managing Risk With Market-Based Instruments
AbstractAccurate pricing of weather derivatives is critically dependent upon correct specification of the underlying weather process. We test among six likely alternative processes using maximum likelihood methods and data from the Fresno, CA weather station. Using these data, we find that the best process is a mean-reverting geometric Brownian process with discrete jumps and ARCH errors. We describe a pricing model for weather derivatives based on such a process.
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Bibliographic InfoPaper provided by NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management in its series 2002 Conference, April 22-23, 2002, St. Louis, Missouri with number 19074.
Date of creation: 2002
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Web page: http://www.agebb.missouri.edu/ncrext/ncr134/
Risk and Uncertainty;
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