Multi-Objective Evolutionary Computation for the Portfolio Optimization Problem with Respect to Environmental, Social, and Governance Criteria

Riley Herman, Malek Mouhoub

2025

Abstract

A common problem facing many is the tension between doing what aligns with our values and doing what is fiscally best. We propose a system leveraging Multi-Objective Evolutionary Computation, specifically MOEA/D, to produce highly performant portfolios tailored to an individual’s Environmental, Social, and Governance (ESG) preferences given a custom survey that we have designed. The survey is conducted to construct a weighting to normalize a given investor’s own responses and allow a single portfolio from the collection of the best portfolios to be matched to that investor. We have adopted two potential architectures to build our proposed system: Architecture 1, where the optimization is run for each investor that takes the survey, and Architecture 2 where a multi-objective optimization is run less frequently and the investor is given a portfolio from the Pareto front. This subset consists of all the non-dominated portfolios. The user may have different experiences, including quality or response time, depending on the architecture chosen. The results of the experiments we conducted demonstrate that both architectures performed comparably and produced high-quality portfolios. However, the best portfolio from Architecture 2 was better in most respects than any portfolio from Architecture 1. All Architecture 1 portfolios were more significantly tailored to each of the individuals’ preferences. For Architecture 2, a limited number of high performing portfolios was generated: as a result, more investors would potentially be recommended to the same few portfolios, especially in comparison to Architecture 1.

Paper Citation

in Harvard Style

Herman R. and Mouhoub M. (2025). Multi-Objective Evolutionary Computation for the Portfolio Optimization Problem with Respect to Environmental, Social, and Governance Criteria. In Proceedings of the 15th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH; ISBN 978-989-758-759-7, SciTePress, pages 357-365. DOI: 10.5220/0013604500003970

in Bibtex Style

@conference{simultech25,
author={Riley Herman and Malek Mouhoub},
title={Multi-Objective Evolutionary Computation for the Portfolio Optimization Problem with Respect to Environmental, Social, and Governance Criteria},
booktitle={Proceedings of the 15th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH},
year={2025},
pages={357-365},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013604500003970},
isbn={978-989-758-759-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH
TI - Multi-Objective Evolutionary Computation for the Portfolio Optimization Problem with Respect to Environmental, Social, and Governance Criteria
SN - 978-989-758-759-7
AU - Herman R.
AU - Mouhoub M.
PY - 2025
SP - 357
EP - 365
DO - 10.5220/0013604500003970
PB - SciTePress