Wind Derivatives: Modeling and Pricing

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 ?nancial 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 ef?cient 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.