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Estimating the Payoffs of Temperature-based Weather Derivatives

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  • Adam Clements

    ()
    (QUT)

  • A S Hurn

    ()
    (QUT)

  • K A Lindsay

    ()
    (Glasgow)

Abstract

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.

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File URL: http://www.ncer.edu.au/papers/documents/NCER_WpNo33Aug08.pdf
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Bibliographic Info

Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 33.

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Length: 18
Date of creation: 26 Aug 2008
Date of revision:
Handle: RePEc:qut:auncer:2008-22

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Related research

Keywords: Temperature; Weather Derivatives; Cooling Degree Days; Time-series Models.;

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  1. Peter Alaton & Boualem Djehiche & David Stillberger, 2002. "On modelling and pricing weather derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(1), pages 1-20.
  2. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
  3. 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.
  4. 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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Cited by:
  1. Adam Clements & A S Hurn & K A Lindsay, 2008. "Developing analytical distributions for temperature indices for the purposes of pricing temperature-based weather derivatives," NCER Working Paper Series 34, National Centre for Econometric Research.
  2. Janda, Karel & Vylezik, Tomas, 2011. "Financial Management of Weather Risk with Energy Derivatives," MPRA Paper 35037, University Library of Munich, Germany.

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