Advancing ESG Portfolio Optimization: Methods, Progress, and Future Directions

Abstract

Objective - The integration of environmental, social, and governance (ESG) criteria into investment portfolios has emerged as a critical field of study, underscoring the interconnectedness between financial markets and global sustainability objectives. Methodology/Technique - This systematic literature review analyzes 157 academic documents, focusing on ESG portfolio optimization methodologies and identifying emerging trends. Key methods reviewed include genetic algorithms, dynamic optimization models, multi-objective optimization frameworks, and machine learning techniques. Findings - Despite considerable advancements, gaps remain, such as the need for broader application across diverse markets and asset classes, improved risk-return assessments, and standardized ESG data reporting. Future research should also investigate the role of central banks and regulators in fostering sustainable finance. Novelty - By addressing these gaps, stakeholders can better align investment practices with sustainability goals, contributing to a more resilient and inclusive global economy. Type of Paper: Review JEL Classification: G11, Q56, G28, G32 Keywords: Sustainable Investment, Sustainable Finance, ESG Portfolio Performance, ESG Risk Management, ESG Portfolio Optimization Reference to this paper should be referred to as follows: Billah, A.L; Koesrindartoto, D.P; Faturohman, T. (2024). Advancing ESG Portfolio Optimization: Methods, Progress, and Future Directions, Acc. Fin. Review, 9(2), 65 – 73. https://doi.org/10.35609/afr.2024.9.2(2)