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Fair Pricing of Weather Derivatives

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Abstract

This paper proposes a consistent benchmark approach to price weather derivatives. The growth optimal portfolio to price weather derivatives. The growth optimal portfolio is used as numeraire such that all benchmarked fair price processes are martingales. No measure transformation is needed for fair pricing. Since weather derivatives are traded in an incomplete market setting, standard hedging based pricing methods cannot be applied. For weather derivative payoffs that are independent from the value of the growth optimal portfolio it is shown that the classical actuarial pricing methodology is a particular case of the fair pricing concept. A discrete time model is constructed to approximate historical weather characteristics assuming Gaussian residuals. For particular weather derivatives their fair prices are derived.

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File URL: http://www.business.uts.edu.au/qfrc/research/research_papers/rp106.pdf
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Paper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 106.

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Date of creation: 01 Sep 2003
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Handle: RePEc:uts:rpaper:106

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Keywords: weather derivatives; benchmark approach; growth optimal portfolio; fair pricing; actuarial pricing;

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  1. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
  2. Takeaki Kariya, 2003. "Weather Risk Swap Valuation," KIER Working Papers 568, Kyoto University, Institute of Economic Research.
  3. I. Bajeux-Besnainou & R. Portait, 1997. "The numeraire portfolio: a new perspective on financial theory," The European Journal of Finance, Taylor & Francis Journals, vol. 3(4), pages 291-309.
  4. Fama, Eugene F & MacBeth, James D, 1974. "Long-Term Growth in a Short-Term Market," Journal of Finance, American Finance Association, vol. 29(3), pages 857-85, June.
  5. Long, John Jr., 1990. "The numeraire portfolio," Journal of Financial Economics, Elsevier, vol. 26(1), pages 29-69, July.
  6. Hans Buhlmann & Eckhard Platen, 2002. "A Discrete Time Benchmark Approach for Finance and Insurance," Research Paper Series 74, Quantitative Finance Research Centre, University of Technology, Sydney.
  7. Eckhard Platen, 2001. "Arbitrage in Continuous Complete Markets," Research Paper Series 72, Quantitative Finance Research Centre, University of Technology, Sydney.
  8. Eckhard Platen, 2003. "Diversified Portfolios in a Benchmark Framework," Research Paper Series 87, Quantitative Finance Research Centre, University of Technology, Sydney.
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Cited by:
  1. Yuji Yamada, 2008. "Optimal Hedging of Prediction Errors Using Prediction Errors," Asia-Pacific Financial Markets, Springer, vol. 15(1), pages 67-95, March.
  2. 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.
  3. Hélène Hamisultane, 2006. "Pricing the Weather Derivatives in the Presence of Long Memory in Temperatures," Working Papers halshs-00079197, HAL.
  4. Eckhard Platen, 2003. "A Benchmark Framework for Risk Management," Research Paper Series 113, Quantitative Finance Research Centre, University of Technology, Sydney.
  5. Adam Clements & A S Hurn & K A Lindsay, 2008. "Estimating the Payoffs of Temperature-based Weather Derivatives," NCER Working Paper Series 33, National Centre for Econometric Research.

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