ESG integration strategy with a multivariate normal distribution

Auteurs-es

DOI :

https://doi.org/10.5902/1983465985183

Mots-clés :

ESG integration, ESG portfolio optimization

Résumé

Purpose: The paper aims to present a new framework for ESG integration strategies in portfolio optimization problems. The optimization in the new structure focuses on the portfolio level, and the procedure is not focused on utility functions or on preliminary weights applied to the asset level. It applies the resampling technique, and all the portfolios are optimal portfolios in the mean-variance space. It uses a filtering process where only optimal portfolios with lower ESG risks are considered. Therefore, this technique works only with optimized portfolios, avoids concentration bias, and considers estimation errors in the expected returns and in the covariance matrix.
Design/methodology/approach: The sample mean returns and covariance matrices generated by a multivariate normal distribution are applied in mean-variance optimization to generate several portfolios in the efficient frontiers. An ESG filtering process is used to select portfolios with lower ESG risks from a sample of 42 companies listed on the Brazilian stock exchange with returns from the period of 2018/01/01 to 2024/04/22.
Findings: Integration strategy costs may be lower than the best-in-class strategy costs and may be similar to the costs of a negative screening strategy.
Social implications: The paper presents a framework that considers social, environmental, and governance factors in the portfolio optimization process.
Originality: The main contribution of this paper is to present a new framework that combines resampling of returns’ mean and covariance based on a multivariate normal distribution with an ESG portfolio filtering process.

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Bibliographies de l'auteur-e

Antonio Francisco de Almeida da Silva Junior, Universidade Federal da Bahia

Postdoctoral fellow as Visiting Researcher at New York University 2015-2016 (Finance and Risk Engineering Department). PhD in Aeronautical and Mechanical Engineering, in 2006, from the Production Engineering department, at the Instituto Tecnológico de Aeronáutica (ITA), with a thesis on exchange rate instructions in financial crises. Graduated in 1988 in Chemical Engineering, completed a master's degree in Engineering in 1998, with a dissertation in the area of ​​Industrial Process Automation, and a master's degree in Administration, in 2000, with a dissertation in the area of ​​market risk management, from the Federal University of Bahia - UFBA. He works at the Central Bank of Brazil in the area of ​​risk management, is an assistant professor at the Faculty of Administration at UFBA, works as a participating professor in the Postgraduate Program in Industrial Engineering, at UFBA, and is a permanent professor at the Postgraduate Center in Administration NPGA-UFBA. His academic works are oriented towards risk management and investment decisions.

Rafael Sidrim Lôpo, Universidade Federal da Bahia

Undergraduated in Business Administration - EAUFBA.

Pedro Henrique Lofiego, Centro Universitário do Leste de Minas Gerais

Undergraduated in Industrial Engineering - PUC Minas.

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Publié-e

2024-07-25

Comment citer

Silva Junior, A. F. de A. da, Lôpo, R. S., & Lofiego, P. H. (2024). ESG integration strategy with a multivariate normal distribution. Revista De Administração Da UFSM, 17(3), e2. https://doi.org/10.5902/1983465985183

Numéro

Vol. 17 No. 3 (2024): Jul-Sep

Rubrique

Articles

Licence

(c) Tous droits réservés Antonio Francisco de Almeida da Silva Junior, Rafael Sidrim Lôpo, Pedro Henrique Lofiego 2024

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Cette œuvre est sous licence Creative Commons Attribution 4.0 International.

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