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Modeling and Hedging Rain Risk

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Author Info
Musshoff, Oliver
Odening, Martin
Xu, Wei

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Abstract

In this article we price a precipitation option based on empirical weather data from Germany using different pricing methods, among them Burn Analysis, Index Value Simulation and Daily Simulation. For that purpose we develop a daily precipitation model. Moreover, a de-correlation analysis is proposed to assess the spatial basis risk that is inherent to rainfall derivatives. The models are applied to precipitation data in Brandenburg, Germany. Based on simplifying assumptions of the production function, we quantify and compare the risk exposure of grain producers with and without rainfall insurance. It turns out that a considerable risk remains with producers who are remotely located from the weather station. Another finding is that significant differences may occur between the pricing methods. We identify the strengths and weaknesses of the pricing methods and give some recommendations for their applications. Our results are relevant for producers as well as for potential sellers of weather derivatives.

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Publisher Info
Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2006 Annual meeting, July 23-26, Long Beach, CA with number 21050.

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Date of creation: 2006
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Handle: RePEc:ags:aaea06:21050

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Related research
Keywords: Risk and Uncertainty;

References listed on IDEAS
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  1. Skees, Jerry & Gober, Stephanie & Varangis, Panos & Lester, Rodney & Kalavakonda, Vijay, 2001. "Developing rainfall-based index insurance in Morocco," Policy Research Working Paper Series 2577, The World Bank. [Downloadable!]
  2. Timothy J. Richards & Mark R. Manfredo & Dwight R. Sanders, 2004. "Pricing Weather Derivatives," American Journal of Agricultural Economics, American Agricultural Economics Association, vol. 86(4), pages 1005-1017, November. [Downloadable!] (restricted)
  3. Turvey, Calum G., 1999. "The Essentials Of Rainfall Derivatives And Insurance," Working Papers 34149, University of Guelph, Department of Food, Agricultural and Resource Economics. [Downloadable!]
  4. Sean D. Campbell & Francis X. Diebold, 2003. "Weather Forecasting for Weather Derivatives," NBER Working Papers 10141, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  5. Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2004. "Pricing Weather Derivatives," Working Papers 28536, Arizona State University, Morrison School of Agribusiness and Resource Management. [Downloadable!]
  6. Peter Alaton & Boualem Djehiche & David Stillberger, 2002. "On modelling and pricing weather derivatives," Applied Mathematical Finance, Taylor and Francis Journals, vol. 9(1), pages 1-20, March. [Downloadable!] (restricted)
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