Modeling and Hedging Rain Risk

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.


Issue Date:
2006
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/21050
Total Pages:
25
Series Statement:
Selected Paper




 Record created 2017-04-01, last modified 2017-08-24

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