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

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.

How to cite

Mraoua, M., and Bari, D. 2007.  Temperature Stochastic Modeling and Weather Derivatives Pricing : Empirical Study With Marrocan Data. Afrika Statistika, Vol.2, n°1, pp.22-43.  DOI:10.4314/afst.v2i1.46865

Fog study in the coastal zone through the modeling of physical processes of the atmospheric boundary layer: Case study of Grand Casablanca (Morocco)


The prediction of fog remains a challenge due to its time and space variability and to the complex interaction between the numerous physical processes influencing its life cycle. During the first stage of this thesis, the local meteorological and synoptic characteristics of fog occurrence over the Grand Casablanca region (Morocco) are investigated. To achieve this, hourly surface meteorological observations, at two synoptic stations of this coastal region, are used. An objective fog-type classification has been developed in this work and used to discriminate the fog events into the well known types. This fog climatology points out that the fog is often localized and that it is predominantly of advection-radiation type, followed by fog resulting from cloud base lowering and radiation fog. Besides, two different fog types can occur when fog simultaneously concerns the two stations. The advective processes associated with sea breeze circulation during the daylight, followed by the radiative processes often leads to fog formation over this coastal region. Numerical simulations are performed later using the meso-scale non-hydrostatic model Meso-NH. These simulations confirm that the physical processes, governing the life cycle of fog, can be different according to the physiographic features of the area. Moreover, the numerical prediction of coastal fog over heterogeneous area is very sensitive to sea surface temperature, land local topography and land cover. It also depends on the model’s ability to reproduce the sea breeze circulation during the daylight followed by the radiative processes early in the night. The systematic numerical simulations of the fog events that occurred during the winter 2013-2014 indicate the Meso-NH’s ability to well capture the fog occurrence with a relatively high false alarm rate, particularly over the coastal station.

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