Forecasting Euro - United States Dollar Exchange Rate with Gene Expression Programming - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2010

Forecasting Euro - United States Dollar Exchange Rate with Gene Expression Programming

Abstract

In the current paper we present the application of our Gene Expression Programming Environment in forecasting Euro-United States Dollar exchange rate. Specifically, using the GEP Environment we tried to forecast the value of the exchange rate using its previous values. The data for the EURO-USD exchange rate are online available from the European Central Bank (ECB). The environment was developed using the JAVA programming language, and is an implementation of a variation of Gene Expression Programming. Gene Expression Programming (GEP) is a new evolutionary algorithm that evolves computer programs (they can take many forms: mathematical expressions, neural networks, decision trees, polynomial constructs, logical expressions, and so on). The computer programs of GEP, irrespective of their complexity, are all encoded in linear chromosomes. Then the linear chromosomes are expressed or translated into expression trees (branched structures). Thus, in GEP, the genotype (the linear chromosomes) and the phenotype (the expression trees) are different entities (both structurally and functionally). This is the main difference between GEP and classical tree based Genetic Programming techniques.
Fichier principal
Vignette du fichier
AntoniouGTL10.pdf (66.84 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01060654 , version 1 (17-11-2017)

Licence

Attribution

Identifiers

Cite

Maria A. Antoniou, Efstratios F. Georgopoulos, Konstantinos A. Theofilatos, Spiridon D. Likothanassis. Forecasting Euro - United States Dollar Exchange Rate with Gene Expression Programming. 6th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations (AIAI), Oct 2010, Larnaca, Cyprus. pp.78-85, ⟨10.1007/978-3-642-16239-8_13⟩. ⟨hal-01060654⟩
79 View
56 Download

Altmetric

Share

Gmail Facebook X LinkedIn More