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

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URI: https://hdl.handle.net/10641/6845
ISSN: 2079-9292
DOI: 10.3390/electronics14132559

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2025-07

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Abstract

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.

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Publisher Copyright: © 2025 by the authors.

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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

Citation

Millán-Palacios, S & Sánchez-Soriano, J 2025, 'Investment Portfolios Optimization with Genetic Algorithm : An Approach Applied to the Spanish Market (IBEX 35)', Electronics (Switzerland), vol. 14, no. 13, 2559. https://doi.org/10.3390/electronics14132559

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ESCUELA POLITÉCNICA SUPERIOR