Modelling and Forecasting Wind Speed Intensity for Weather Risk Management

Abstract

The modeling of wind speed is a traditional topic in meteorological researches where the main interest is on the short term forecast of wind speed intensity and direction. More recently this theme has received some interest in the quantitative finance literature for its relations with the electricity production by wind farms. In fact, electricity producers are interested in long range forecasts and simulation of wind speed for two main reasons: to evaluate the profitability of a wind farm to be built in a given location, and to offset the risks associated with the variability of wind speed for an already operating wind farm. In this paper we contribute to the increasing literature of environmental finance by comparing three approaches capable to forecast and simulate the long run evolution of wind speed intensity (direction is not a concern given that the recent turbines can rotate to follow wind speed): the Auto Regressive Gamma process, the Gamma Auto Regressive process, and the ARFIMA-FIGARCH model. We provide both in-sample and out-of-sample comparison of the models as well as some examples for the pricing of wind speed derivatives using a model based Monte Carlo simulation approach.

Keywords: Gamma Auto Regressive, Auto Regressive Gamma, ARFIMA-FIGARCH, wind speed modeling, wind speed simulation

JEL Classification: C22, C53, G17, G13, G22