Combinatorial Nonlinear Goal Programming for ESG Portfolio Optimization and Dynamic Hedge Management

Dash, Gordon H.; Kajiji, Nina

doi:10.1007/978-3-319-05014-0_18

Mathematical and Statistical Methods for Actuarial Sciences and Finance 2014

DOI: 10.1007/978-3-319-05014-0_18

|View full text |Cite

Combinatorial Nonlinear Goal Programming for ESG Portfolio Optimization and Dynamic Hedge Management

Gordon H. Dash

Nina Kajiji

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

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

Billah,

Koesrindartoto,

Faturohman

2024

Acc. Fin. Review

View full text Add to dashboard Cite

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)

show abstract

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

Billah,

Koesrindartoto,

Faturohman

2024

Acc. Fin. Review

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Combinatorial Nonlinear Goal Programming for ESG Portfolio Optimization and Dynamic Hedge Management

Cited by 1 publication

References 6 publications

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

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

Contact Info

Product

Resources

About