Estimating the Payoffs of Temperature-based Weather Derivatives
Temperature-based weather derivatives are written on an index which is normally defined to be a nonlinear function of average daily temperatures. Recent empirical work has demonstrated the usefulness of simple time-series models of temperature for estimating the payoffs to these instruments. This paper argues that a more direct and parsimonious approach is to model the time-series behaviour of the index itself, provided a sufficiently rich supply of historical data is available. A data set comprising average daily temperature spanning over a hundred years for four Australian cities is assembled. The data is then used to compare the actual payoffs of temperature-based European call options with the expected payoffs computed from historical temperature records and two time-series approaches. It is concluded that expected payoffs computed directly from historical records perform poorly by comparison with the expected payoffs generated by means of competing time-series models. It is also found that modeling the relevant temperature index directly is superior to modeling average daily temperatures.
|Date of creation:||26 Aug 2008|
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- Fred Espen Benth & Jurate Saltyte-Benth, 2005. "Stochastic Modelling of Temperature Variations with a View Towards Weather Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(1), pages 53-85.
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- Sean D. Campbell & Francis X. Diebold, 2002.
"Weather Forecasting for Weather Derivatives,"
Center for Financial Institutions Working Papers
02-42, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Sean D. Campbell & Francis X. Diebold, 2003. "Weather Forecasting for Weather Derivatives," NBER Working Papers 10141, National Bureau of Economic Research, Inc.
- Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
- Eckhard Platen & Jason West, 2003.
"Fair Pricing of Weather Derivatives,"
Research Paper Series
106, Quantitative Finance Research Centre, University of Technology, Sydney.
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