Weather Derivative Pricing with Nonlinear Weather Forecasting

In recent years we witnessed a rapid growth of weather derivatives market. These derivatives are used to hedge energy contracts and distribute weather risk. While most derivative markets are complete and contingent climes replications are standard procedure, this special market is incomplete, and therefore modeling the weather is a more appropriate approach to pricing. In this work we base our modeling on a widely accepted physical approach, we use Navier-Stokes equations applied to a thin atmosphere as presented by Lorentz 1962. This modeling is considered by meteorologists a “very-long-weather” prediction, allows for an accurate and robust temperature forecasting. We show that under this setting we empirically outperform the standard approach to weather derivative pricing