Temperature stochastic modeling and weather derivatives pricing: empirical study with Moroccan data

Abstract

The main objective of this paper is to present a price model for weather derivatives with payouts depending on temperature. We start by using the method of Principal Component Analysis (PCA) to fill the missing temperature data, after what, we determine by using a statistical approach the cold and the warm periods on the area of Casablanca. Then, we use 44 years of daily historical data to apply a stochastic process to describe the evolution of the temperature. A numerical example showing the pricing of a swap contract is presented, using an approximation formula as well as Monte Carlo simulations.