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Pricing weather derivatives by marginal value

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  • M. Davis
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    Abstract

    Weather derivatives are a classic incomplete market. This paper gives a preliminary exploration of weather derivative pricing using the 'marginal substitution value' or 'shadow price' approach of mathematical economics. Accumulated heating degree days (HDD) and commodity prices are modelled as geometric Brownian motion, leading to explicit expressions for swap rates and option values.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/713665730
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    Bibliographic Info

    Article provided by Taylor and Francis Journals in its journal Quantitative Finance.

    Volume (Year): 1 (2001)
    Issue (Month): 3 ()
    Pages: 305-308

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    Handle: RePEc:taf:quantf:v:1:y:2001:i:3:p:305-308

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    Cited by:
    1. Dupuis, Debbie J., 2011. "Forecasting temperature to price CME temperature derivatives," International Journal of Forecasting, Elsevier, vol. 27(2), pages 602-618, April.
    2. 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.
    3. Musshoff, Oliver & Odening, Martin & Xu, Wei, 2005. "Zur Bewertung von Wetterderivaten als innovative Risikomanagementinstrumente in der Landwirtschaft," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 54(4).
    4. 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.
    5. Svec, J. & Stevenson, M., 2007. "Modelling and forecasting temperature based weather derivatives," Global Finance Journal, Elsevier, vol. 18(2), pages 185-204.
    6. 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.
    7. Yong-Jin Kim, 2004. "Good-Deal Option Price Bounds for a Non-Traded Event with Stochastic Return: A Note," Asia-Pacific Financial Markets, Springer, vol. 11(2), pages 135-141, June.
    8. Taylor, James W. & Buizza, Roberto, 2006. "Density forecasting for weather derivative pricing," International Journal of Forecasting, Elsevier, vol. 22(1), pages 29-42.
    9. Traian A. Pirvu & Huayue Zhang, 2012. "A Multi Period Equilibrium Pricing Model," Papers 1205.6193, arXiv.org.
    10. Turvey, Calum G. & Norton, Michael T., 2008. "An Internet-Based Tool for Weather Risk Management," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(1), April.
    11. Massimiliano Caporin & Juliusz Pres' & Hipolit Torro, 2010. "Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options," "Marco Fanno" Working Papers 0123, Dipartimento di Scienze Economiche "Marco Fanno".
    12. Kanamura, Takashi & Ohashi, Kazuhiko, 2009. "Pricing summer day options by good-deal bounds," Energy Economics, Elsevier, vol. 31(2), pages 289-297, March.
    13. Fuhrer, Jurg & Beniston, Martin & Calanca, Pierluigi & Torriani, Daniele Simone, 2007. "Alternative Hedging Strategies in Maize Production to Cope with Climate Variability and Change," 101st Seminar, July 5-6, 2007, Berlin Germany 9275, European Association of Agricultural Economists.
    14. Mulong Wang & Min-Ming Wen & Charles C. Yang, 2010. "Weather derivatives, price forwards, and corporate risk management," Journal of Risk Finance, Emerald Group Publishing, vol. 11(4), pages 358-376, August.
    15. Geyser, J.M., 2004. "Weather derivatives: Concept and application for their use in South Africa," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 43(4), December.
    16. Xu, Wei & Odening, Martin & Musshoff, Oliver, 2007. "Indifference Pricing of Weather Insurance," 101st Seminar, July 5-6, 2007, Berlin Germany 9267, European Association of Agricultural Economists.
    17. Yuji Yamada, 2008. "Optimal Hedging of Prediction Errors Using Prediction Errors," Asia-Pacific Financial Markets, Springer, vol. 15(1), pages 67-95, March.
    18. Sébastien Chaumont & Peter Imkeller & Matthias Müller & Ulrich Horst, 2005. "A Simple Model for Trading Climate Risk," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 74(2), pages 175-195.
    19. Cyr, Don & Kusy, Martin, 2007. "Identification of stochastic processes for an estimated icewine temperature hedging variable," Working Papers 37298, American Association of Wine Economists.

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