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Utility-based Pricing of the Weather Derivatives

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  • Hélène Hamisultane

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

Since the underlying of the weather derivatives is not a traded asset, these contracts cannot be evaluated by the traditional financial theory. Cao and Wei (2004) price them by using the consumption-based asset pricing model of Lucas (1978) and by assuming different values for the constant relative risk aversion coefficient. Instead of taking this coefficient as given, we suggest in this paper to estimate it by using the consumption data and the quotations of one of the most transacted weather contracts which is the New York weather futures on the Chicago Mercantile Exchange (CME). We apply the well-known generalized method of moments (GMM) introduced by Hansen (1982) to estimate it as well as the simulated method of moments (SMM) attributed to Lee and Ingram (1991) and Duffie and Singleton (1993). This last method is studied since it is presumed to give satisfactory results in the case of the weather derivatives for which the prices are simulated. We find that the estimated coefficient from the SMM approach must have improbably high values in order to have the calculated weather futures prices matching the observations.

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  • Hélène Hamisultane, 2007. "Utility-based Pricing of the Weather Derivatives," Working Papers halshs-00088701, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00088701
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00088701v2
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    1. Dorfleitner, Gregor & Wimmer, Maximilian, 2010. "The pricing of temperature futures at the Chicago Mercantile Exchange," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1360-1370, June.
    2. Gülpınar, Nalân & Çanakoḡlu, Ethem, 2017. "Robust portfolio selection problem under temperature uncertainty," European Journal of Operational Research, Elsevier, vol. 256(2), pages 500-523.
    3. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    4. Hélène Hamisultane, 2008. "Which Method for Pricing Weather Derivatives ?," Working Papers halshs-00355856, HAL.

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