Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79601
Authors: 
López Cabrera, Brenda
Odening, Martin
Ritter, Matthias
Year of Publication: 
2013
Series/Report no.: 
SFB 649 Discussion Paper 2013-005
Abstract: 
Many business people such as farmers and financial investors are affected by indirect losses caused by scarce or abundant rainfall. Because of the high potential of insuring rainfall risk, the Chicago Mercantile Exchange (CME) began trading rainfall derivatives in 2011. Compared to temperature derivatives, however, pricing rainfall derivatives is more difficult. In this article, we propose to model rainfall indices via a flexible type of distribution, namely the normal-inverse Gaussian distribution, which captures asymmetries and heavy-tail behaviour. The prices of rainfall futures are computed by employing the Esscher transform, a wellknown tool in actuarial science. This approach is flexible enough to price any rainfall contract and to adjust theoretical prices to market prices by using the calibrated market price of risk. This empirical analysis is conducted with U.S. precipitation data and CME futures data providing first results on the market price of risk for rainfall derivatives.
Subjects: 
weather derivatives
precipitation
Esscher transform
market price of risk
JEL: 
G19
G29
G22
Q59
Document Type: 
Working Paper

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