Wind Derivatives: Modeling and Pricing

Authors:
A. Alexandridis;A. Zapranis
Affiliations:
School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, UK CT2 7NF;Department of Accounting and Finance, University of Macedonia of Economics and Social Studies, Thessaloniki, Greece 54006
Venue:
Computational Economics
Year:
2013

Citing 4
Cited 0

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Abstract

Wind is considered to be a free, renewable and environmentally friendly source of energy. However, wind farms are exposed to excessive weather risk since the power production depends on the wind speed, the wind direction and the wind duration. This risk can be successfully hedged using a financial instrument called weather derivatives. In this study the dynamics of the wind generating process are modeled using a non-parametric non-linear wavelet network. Our model is validated in New York. The proposed methodology is compared against alternative methods, proposed in prior studies. Our results indicate that wavelet networks can model the wind process very well and consequently they constitute an accurate and efficient tool for wind derivatives pricing. Finally, we provide the pricing equations for wind futures written on two indices, the cumulative average wind speed index and the Nordix wind speed index.