Title: Estimate of stochastic model parameter of exchange rate using machine learning techniques

Authors: El Hachloufi Mostafa; Faris Hamza; El Haddad Mohammed

Addresses: Faculty of Law Economics and Social Sciences-Agdal, University of Mohamed IV, Rabat, Morocco ' Faculty of Law, Economics and Social Sciences-Tetouan, University of Abdel Malek Essaâdi, Tetouan, Morocco ' Faculty of Law Economics and Social Sciences-Agdal, University of Mohamed IV, Rabat, Morocco

Abstract: In this paper, we present a new approach for estimating the stochastic model parameter of exchange rate using genetic algorithms and neural networks. This approach takes in consideration the minimisation of exchange rate risk that is measured by the conditional value at risk CVaR in the estimation procedure of this parameter. The objective of this approach is to provide a tool of decision for the exchange market managers.

Keywords: exchange rates; estimation; risk; CVaR; stochastic model; genetic algorithms; neural networks.

DOI: 10.1504/IJCAT.2019.101175

International Journal of Computer Applications in Technology, 2019 Vol.60 No.4, pp.326 - 332

Received: 30 May 2017
Accepted: 25 Apr 2018
Published online: 26 Jul 2019 *

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