TY  - Type of reference 
TI  - Optimization of foreign exchange risk hedging by the genetic algorithm 
AU  - Norelislam El Hami 
AU  - Sara Rhouas 
AU  - Mustapha Bouchekourte 
AB  - Researchers and scientific developers today have a huge amount of data to process, they need a solution as quickly as possible, which is why they have developed this metaheuristic based on natural genetic evolution. The genetic algorithm does not take into account all the alternatives, but it is a quick technique to find a decent solution to problems with a lot of data. In many areas, data must be processed as quickly as possible and in this article we have discussed a new way to find the optimum coverage ratio for futures contracts, with the objective of decreasing the risk that one must face in the derivatives market, against fluctuations in the prices of any underlying asset of the futures contracts either commodities, exchange rates or stock market indices ..., in our case we have chosen oil as an example of an application on the fluctuation of commodity prices of a 10-year data margin, by applying the Ederington variance minimization hedge model as an objective function of our genetic optimization algorithm on MATLAB software. 
DO  - 10.21494/ISTE.OP.2022.0786 
JF  - Uncertainties and Reliability of Multiphysical Systems 
KW  - Metaheuristic,  Genetic Algorithm,  foreign Exchange risk, Métaheuristiques,  Algorithme génétique,  risque de change,  
L1  - http://www.openscience.fr/IMG/pdf/iste_incertfia21v5n2_4.pdf 
LA  - en 
PB  - ISTE OpenScience 
DA  - 2022/01/25 
SN  - 2514-569X 
TT  - Optimisation de la couverture du risque de change par l’algorithme génétique 
UR  - http://www.openscience.fr/Optimization-of-foreign-exchange-risk-hedging-by-the-genetic-algorithm 
IS  - Issue 2 
VL  - 5 
ER  -