ESG integration strategy with a multivariate normal distribution
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2024 |
| Outros Autores: | , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Revista de Administração da UFSM |
| Texto Completo: | https://periodicos.ufsm.br/reaufsm/article/view/85183 |
Resumo: | 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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ESG integration strategy with a multivariate normal distributionEstratégia de integração ESG com uma distribuição normal multivariadaESG integrationESG portfolio optimizationIntegração ESGotimização ESG de carteirasPurpose: 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.Finalidade: Este artigo apresenta uma abordagem para a estratégia de integração ESG no problema da otimização usando a técnica de reamostragem. A abordagem não utiliza funções de utilidade ou pesos preliminares no nível do ativo, focando nas carteiras. As carteiras são ótimas no espaço de média-variância, para cada amostra de retornos esperados e matriz de covariância. No processo de filtragem, são selecionadas as carteiras com menor risco ESG. Essa técnica trabalha somente com carteiras otimizadas, evita o viés de concentração (poucos ativos na carteira) e considera erros de estimativa nos retornos esperados e na matriz de covariância.Desenho/metodologia/abordagem: As amostras de retornos médios e matrizes de covariância geradas por uma distribuição normal multivariada são aplicadas na otimização média-variância para gerar várias carteiras nas fronteiras eficientes. É utilizado um processo de filtragem ESG para selecionar carteiras com menores riscos ESG de uma amostra com 42 empresas listadas na B3 com retornos no período de 2018/01/01 a 2023/12/31.Constatações: Os custos da estratégia de integração podem ser inferiores aos custos da estratégia “best-in-class” e podem ser semelhantes aos custos de uma estratégia de “negative screening”, dependendo dos parâmetros de ambas as estratégias. Implicações sociais: O artigo apresenta uma abordagem que considera fatores sociais, ambientais e de governança no processo de otimização de carteiras.Originalidade: A principal contribuição deste artigo é a apresentação de uma nova abordagem que combina a reamostragem da média e covariância dos retornos com base numa distribuição normal multivariada com um processo de filtragem de carteiras ESG.Universidade Federal de Santa Maria2024-07-25info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/xmlhttps://periodicos.ufsm.br/reaufsm/article/view/8518310.5902/1983465985183Revista de Administração da UFSM; Vol. 17 No. 3 (2024): Jul-Sep; e2Revista de Administração da UFSM; Vol. 17 Núm. 3 (2024): Jul-Sep; e2Revista de Administração da UFSM; v. 17 n. 3 (2024): Jul-Set; e21983-46591983-4659reponame:Revista de Administração da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMenghttps://periodicos.ufsm.br/reaufsm/article/view/85183/64010https://periodicos.ufsm.br/reaufsm/article/view/85183/67563Copyright (c) 2024 Antonio Francisco de Almeida da Silva Junior, Rafael Sidrim Lôpo, Pedro Henrique Lofiegoinfo:eu-repo/semantics/openAccessSilva Junior, Antonio Francisco de Almeida daLôpo, Rafael SidrimLofiego, Pedro Henrique2025-07-10T18:40:00Zoai:ojs.pkp.sfu.ca:article/85183Revistahttps://periodicos.ufsm.br/reaufsm/indexPUBhttps://periodicos.ufsm.br/reaufsm/oairea@ufsm.br || centraldeperiodicos@ufsm.br1983-46591983-4659opendoar:2025-07-10T18:40Revista de Administração da UFSM - Universidade Federal de Santa Maria (UFSM)false |
| dc.title.none.fl_str_mv |
ESG integration strategy with a multivariate normal distribution Estratégia de integração ESG com uma distribuição normal multivariada |
| title |
ESG integration strategy with a multivariate normal distribution |
| spellingShingle |
ESG integration strategy with a multivariate normal distribution Silva Junior, Antonio Francisco de Almeida da ESG integration ESG portfolio optimization Integração ESG otimização ESG de carteiras |
| title_short |
ESG integration strategy with a multivariate normal distribution |
| title_full |
ESG integration strategy with a multivariate normal distribution |
| title_fullStr |
ESG integration strategy with a multivariate normal distribution |
| title_full_unstemmed |
ESG integration strategy with a multivariate normal distribution |
| title_sort |
ESG integration strategy with a multivariate normal distribution |
| author |
Silva Junior, Antonio Francisco de Almeida da |
| author_facet |
Silva Junior, Antonio Francisco de Almeida da Lôpo, Rafael Sidrim Lofiego, Pedro Henrique |
| author_role |
author |
| author2 |
Lôpo, Rafael Sidrim Lofiego, Pedro Henrique |
| author2_role |
author author |
| dc.contributor.author.fl_str_mv |
Silva Junior, Antonio Francisco de Almeida da Lôpo, Rafael Sidrim Lofiego, Pedro Henrique |
| dc.subject.por.fl_str_mv |
ESG integration ESG portfolio optimization Integração ESG otimização ESG de carteiras |
| topic |
ESG integration ESG portfolio optimization Integração ESG otimização ESG de carteiras |
| description |
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. |
| publishDate |
2024 |
| dc.date.none.fl_str_mv |
2024-07-25 |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
https://periodicos.ufsm.br/reaufsm/article/view/85183 10.5902/1983465985183 |
| url |
https://periodicos.ufsm.br/reaufsm/article/view/85183 |
| identifier_str_mv |
10.5902/1983465985183 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
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https://periodicos.ufsm.br/reaufsm/article/view/85183/64010 https://periodicos.ufsm.br/reaufsm/article/view/85183/67563 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf text/xml |
| dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
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Universidade Federal de Santa Maria |
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Revista de Administração da UFSM; Vol. 17 No. 3 (2024): Jul-Sep; e2 Revista de Administração da UFSM; Vol. 17 Núm. 3 (2024): Jul-Sep; e2 Revista de Administração da UFSM; v. 17 n. 3 (2024): Jul-Set; e2 1983-4659 1983-4659 reponame:Revista de Administração da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
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Universidade Federal de Santa Maria (UFSM) |
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UFSM |
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Revista de Administração da UFSM |
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Revista de Administração da UFSM |
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Revista de Administração da UFSM - Universidade Federal de Santa Maria (UFSM) |
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rea@ufsm.br || centraldeperiodicos@ufsm.br |
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1847221542902038528 |