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Genetic algorithms and Darwinian approaches in financial applications: A survey

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 42, Issue 21, Pages 7684-7697

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2015.06.001

Keywords

Genetic algorithms; Evolutionary computation; Finance; Portfolio optimization; Survey

Funding

  1. Research Group with Strategic Focus on Intelligent Systems of the National School of Engineering and Sciences at the Tecnologico de Monterrey
  2. Consejo Nacional de Ciencia y Tecnologia (CONACyT) through the PNPC

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This article presents a review of the application of evolutionary computation methods to solving financial problems. Genetic algorithms, genetic programming, multi-objective evolutionary algorithms, learning classifier systems, co-evolutionary approaches, and estimation of distribution algorithms are the techniques considered. The novelty of our approach comes in three different manners: it covers time lapses not included in other review articles, it covers problems not considered by others, and the scope covered by past and new references is compared and analyzed. The results concluded the interest about methods and problems has changed through time. Although, genetic algorithms have remained the most popular approach in the literature. There are combinations of problems and solutions methods which are yet to be investigated. (C) 2015 Elsevier Ltd. All rights reserved.

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