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Weather Derivatives: Managing Risk With Market-Based Instruments

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  • Richards, Timothy J.
  • Manfredo, Mark R.
  • Sanders, Dwight R.

Abstract

Accurate 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.

Suggested Citation

  • Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2002. "Weather Derivatives: Managing Risk With Market-Based Instruments," 2002 Conference, April 22-23, 2002, St. Louis, Missouri 19074, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  • Handle: RePEc:ags:ncrtwo:19074
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    File URL: http://purl.umn.edu/19074
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    References listed on IDEAS

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    Cited by:

    1. Hao, Jianqiang & Hartell, Jason G. & Skees, Jerry R., 2004. "Optimal Inter-Period Weighting of Cumulative Indices for Weather-Based Contingent Claims," 2004 Annual meeting, August 1-4, Denver, CO 19926, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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    Keywords

    Risk and Uncertainty;

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