WEATHER DERIVATIVES: MANAGING RISK WITH MARKET-BASED INSTRUMENTS

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.


Issue Date:
2002
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/19074
Total Pages:
17
Series Statement:
2002 Conference, St. Louis, Missouri, April 22-23




 Record created 2017-04-01, last modified 2017-09-23

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