Investment Portfolios Optimization with Genetic Algorithm : An Approach Applied to the Spanish Market (IBEX 35)

The results of this study validate the use of single-objective genetic algorithms as an effective tool for portfolio optimization in the Spanish market. Through an evolutionary approach with advanced objective functions and a phased structure (training, validation, and testing), the quality and stab...

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Detalles Bibliográficos
Autores: Millán-Palacios, Sandra, Sánchez-Soriano, Javier
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad de Málaga
Repositorio:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
Idioma:inglés
OAI Identifier:oai:ddfv.ufv.es:10641/6845
Acceso en línea:https://hdl.handle.net/10641/6845
Access Level:acceso abierto
Palabra clave:ESG criteria
IBEX 35
artificial intelligence
automated quantitative investing
genetic algorithms
objective function
portfolio optimization
robust portfolio construction
Control and Systems Engineering
Signal Processing
Hardware and Architecture
Computer Networks and Communications
Electrical and Electronic Engineering
Yes
yes
Descripción
Sumario:The results of this study validate the use of single-objective genetic algorithms as an effective tool for portfolio optimization in the Spanish market. Through an evolutionary approach with advanced objective functions and a phased structure (training, validation, and testing), the quality and stability of the generated portfolios were significantly improved. The single-objective genetic algorithms with a Complex Objective Function (SGA-COF-1) model delivered outstanding returns with high robustness and were adaptable to different risk profiles, including the ESG criteria. These contributions open multiple future research directions, such as the incorporation of predictive models, expansion to international markets, and the use of more sophisticated evolutionary algorithms. The proposed methodological framework (flexible and scalable) provides a solid foundation for the development of automated and sustainable quantitative investment solutions.