Afrika Statistika

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

Mohammed Mraoua and Driss Bari

Full-text: Open access

Abstract

The main objective of this paper is to present a technique for pricing weather derivatives with payout depending on temperature. We start by using the Principle Component Analysis method to fill missing temperature data. Consequently, the cold and the warm periods were determined on the basis of a “clean” data by using a statistical approach. After that, we use historical data over a sufficient period to apply a stochastic process that describes the evolution of the temperature. A numerical example of a swap contract pricing is presented, using an approximation formula as well as Monte Carlo simulations.

Article information

Source
Afr. Stat. Volume 2, Number 1 (2007), 22-43.

Dates
Received: April 2007
Accepted: 20 July 2007
First available in Project Euclid: 26 May 2017

Permanent link to this document
https://projecteuclid.org/euclid.as/1495766685

Digital Object Identifier
doi:10.4314/afst.v2i1.46865

Mathematical Reviews number (MathSciNet)
MR2388961

Subjects
Primary: 60H30: Applications of stochastic analysis (to PDE, etc.)
Secondary: 60H10: Stochastic ordinary differential equations [See also 34F05] 65C05: Monte Carlo methods

Keywords
Weather derivatives temperature stochastic model Monte Carlo simulation

Citation

Mraoua, Mohammed; Bari, Driss. Temperature stochastic modeling and weather derivatives pricing: empirical study with Moroccan data. Afr. Stat. 2 (2007), no. 1, 22--43. doi:10.4314/afst.v2i1.46865. https://projecteuclid.org/euclid.as/1495766685


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