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ESG-driven optimal portfolio selection for separated environmental, social, and governance preferences

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  • Tomer Shushi

    (Ben-Gurion University of the Negev)

Abstract

We propose and examine the optimal portfolio selection problem when the investor has different preferences in each of the portfolio’s environmental, social, and governance (ESG) average scores. We provide an explicit formula for the optimal weights in the case of the mean-variance model subject to the E, S, and G constraints and show that the same formula also holds in the case of other models that minimize a risk measure of the portfolio, with focusing on the tail-value-at-risk measure. We show that such models that go beyond the mean-variance model have the same formula for the optimal weight but with an effective risk aversion parameter that depends on the E, S, and G preferences of the investor, unlike in the original mean-variance model where the risk aversion is an external parameter. We then provide some numerical illustrations based on ten stocks from the NASDAQ, which offers clear guidance for allocating the portfolio between the different stocks and shows how each stock is sensitive to changes in the E, S, and G constraints.

Suggested Citation

  • Tomer Shushi, 2025. "ESG-driven optimal portfolio selection for separated environmental, social, and governance preferences," Operational Research, Springer, vol. 25(2), pages 1-12, June.
    • Handle: RePEc:spr:operea:v:25:y:2025:i:2:d:10.1007_s12351-025-00907-3
    DOI: 10.1007/s12351-025-00907-3
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    References listed on IDEAS

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    1. Jan De Spiegeleer & Stephan Höcht & Daniel Jakubowski & Sofie Reyners & Wim Schoutens, 2023. "ESG: a new dimension in portfolio allocation," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 13(2), pages 827-867, April.
    2. Pedersen, Lasse Heje & Fitzgibbons, Shaun & Pomorski, Lukasz, 2021. "Responsible investing: The ESG-efficient frontier," Journal of Financial Economics, Elsevier, vol. 142(2), pages 572-597.
    3. Hamza Hanbali & Daniël Linders & Jan Dhaene, 2023. "Value-at-Risk, Tail Value-at-Risk and upper tail transform of the sum of two counter-monotonic random variables," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2023(3), pages 219-243, March.
    4. Landsman, Zinoviy & Makov, Udi & Shushi, Tomer, 2016. "Tail conditional moments for elliptical and log-elliptical distributions," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 179-188.
    5. Roorda, Berend & Schumacher, J.M., 2007. "Time consistency conditions for acceptability measures, with an application to Tail Value at Risk," Insurance: Mathematics and Economics, Elsevier, vol. 40(2), pages 209-230, March.
    6. Z. Landsman & U. Makov & T. Shushi, 2020. "Portfolio Optimization by a Bivariate Functional of the Mean and Variance," Journal of Optimization Theory and Applications, Springer, vol. 185(2), pages 622-651, May.
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