ESG Portfolio Optimization: The Relevance of Higher Order Moments.
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| Title: | ESG Portfolio Optimization: The Relevance of Higher Order Moments. |
|---|---|
| Authors: | León‐Camacho, Bernardo1 (AUTHOR), Perote, Javier2 (AUTHOR), Mora‐Valencia, Andrés3 (AUTHOR), Zapata‐Quimbayo, Carlos Andrés4 (AUTHOR) carlosa.zapata@uexternado.edu.co |
| Source: | Corporate Social Responsibility & Environmental Management. Nov2025, Vol. 32 Issue 6, p8161-8181. 21p. |
| Subject Terms: | *Sustainability, *Environmental responsibility, Portfolio management (Investments), Modern portfolio theory (Investments), Financial performance, Statistical bias, Cumulants, Kurtosis |
| Abstract: | Environmental, social, and governance (ESG) factors have become key factors in modern portfolio management, shaping how investors think and how they allocate their assets. At the same time, the presence of asymmetric and heavy‐tailed return distributions highlights the necessity of moving beyond the classical mean–variance (MV) framework by incorporating higher‐order moments, such as skewness and kurtosis, into portfolio optimization. To address this issue, we introduce a unified mean–variance‐skewness‐kurtosis‐ESG (MVSK‐ESG) optimization model. This model uses different ESG score thresholds and focuses on ESG leaders within the Dow Jones Industrial Average and the Nasdaq 100. This model incorporates ESG scores into the objective function using a difference‐of‐convex programming framework to address the model's inherent nonconvexity. Empirical results show that MVSK‐ESG portfolios consistently outperform traditional MV and ESG‐constrained portfolios as well as their benchmarks, with higher risk‐adjusted returns. The proposed framework provides a robust approach for integrating sustainability considerations into portfolio construction. [ABSTRACT FROM AUTHOR] |
| Copyright of Corporate Social Responsibility & Environmental Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
| FullText | Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 189104288 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: ESG Portfolio Optimization: The Relevance of Higher Order Moments. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22León‐Camacho%2C+Bernardo%22">León‐Camacho, Bernardo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Perote%2C+Javier%22">Perote, Javier</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mora‐Valencia%2C+Andrés%22">Mora‐Valencia, Andrés</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zapata‐Quimbayo%2C+Carlos+Andrés%22">Zapata‐Quimbayo, Carlos Andrés</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> carlosa.zapata@uexternado.edu.co</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Corporate+Social+Responsibility+%26+Environmental+Management%22">Corporate Social Responsibility & Environmental Management</searchLink>. Nov2025, Vol. 32 Issue 6, p8161-8181. 21p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+responsibility%22">Environmental responsibility</searchLink><br /><searchLink fieldCode="DE" term="%22Portfolio+management+%28Investments%29%22">Portfolio management (Investments)</searchLink><br /><searchLink fieldCode="DE" term="%22Modern+portfolio+theory+%28Investments%29%22">Modern portfolio theory (Investments)</searchLink><br /><searchLink fieldCode="DE" term="%22Financial+performance%22">Financial performance</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+bias%22">Statistical bias</searchLink><br /><searchLink fieldCode="DE" term="%22Cumulants%22">Cumulants</searchLink><br /><searchLink fieldCode="DE" term="%22Kurtosis%22">Kurtosis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Environmental, social, and governance (ESG) factors have become key factors in modern portfolio management, shaping how investors think and how they allocate their assets. At the same time, the presence of asymmetric and heavy‐tailed return distributions highlights the necessity of moving beyond the classical mean–variance (MV) framework by incorporating higher‐order moments, such as skewness and kurtosis, into portfolio optimization. To address this issue, we introduce a unified mean–variance‐skewness‐kurtosis‐ESG (MVSK‐ESG) optimization model. This model uses different ESG score thresholds and focuses on ESG leaders within the Dow Jones Industrial Average and the Nasdaq 100. This model incorporates ESG scores into the objective function using a difference‐of‐convex programming framework to address the model's inherent nonconvexity. Empirical results show that MVSK‐ESG portfolios consistently outperform traditional MV and ESG‐constrained portfolios as well as their benchmarks, with higher risk‐adjusted returns. The proposed framework provides a robust approach for integrating sustainability considerations into portfolio construction. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Corporate Social Responsibility & Environmental Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/csr.70122 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 8161 Subjects: – SubjectFull: Sustainability Type: general – SubjectFull: Environmental responsibility Type: general – SubjectFull: Portfolio management (Investments) Type: general – SubjectFull: Modern portfolio theory (Investments) Type: general – SubjectFull: Financial performance Type: general – SubjectFull: Statistical bias Type: general – SubjectFull: Cumulants Type: general – SubjectFull: Kurtosis Type: general Titles: – TitleFull: ESG Portfolio Optimization: The Relevance of Higher Order Moments. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: León‐Camacho, Bernardo – PersonEntity: Name: NameFull: Perote, Javier – PersonEntity: Name: NameFull: Mora‐Valencia, Andrés – PersonEntity: Name: NameFull: Zapata‐Quimbayo, Carlos Andrés IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 15353958 Numbering: – Type: volume Value: 32 – Type: issue Value: 6 Titles: – TitleFull: Corporate Social Responsibility & Environmental Management Type: main |
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