WEATHER DERIVATIVES: MANAGING RISK WITH MARKET-BASED INSTRUMENTS

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dc.creatorRichards, Timothy J.
dc.creatorManfredo, Mark R.
dc.creatorSanders, Dwight R.
dc.date2017-04-01T13:54:54Z
dc.date.accessioned2026-07-09T03:26:27Z
dc.descriptionAccurate 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.
dc.identifierdoi:10.22004/ag.econ.19074
dc.identifierhttps://ageconsearch.umn.edu/record/19074/files/cp01ri01.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/19074
dc.identifier.urihttp://hdl.handle.net/123456789/532604
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/19074
dc.titleWEATHER DERIVATIVES: MANAGING RISK WITH MARKET-BASED INSTRUMENTS
dc.typeText

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