Environmental, Social and Governance-Valued Portfolio Optimization and Dynamic Asset Pricing

Davide Lauria, W. Brent Lindquist (), Stefan Mittnik and Svetlozar T. Rachev
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Davide Lauria: Department of Economics, Statistics and Finance, University of Calabria, 87036 Rende, CS, Italy
W. Brent Lindquist: Department of Mathematics & Statistics, Texas Tech University, Lubbock, TX 79409-1042, USA
Stefan Mittnik: Scalable Capital, 80538 Müchen, Germany
Svetlozar T. Rachev: Department of Mathematics & Statistics, Texas Tech University, Lubbock, TX 79409-1042, USA

JRFM, 2025, vol. 18, issue 3, 1-33

Abstract: Environmental, social and governance (ESG) ratings (scores) provide quantitative measures for socially responsible investment. We consider ESG scores to be a third independent variable—on par with financial risk and return—and incorporate such numeric scores into dynamic asset pricing. Based on this incorporation, we develop the entire investment process for the ESG market: portfolio optimization and efficient frontier, capital market line (the market portfolio), risk-assessment measures and hedging instruments (options). There is currently no riskless asset available in such an ESG market; to address this, we develop the so-called shadow riskless rate, applicable to markets having only risky assets. We believe this to be the first paper that fully develops, under a single dynamic pricing framework, the entire investment process for an ESG market. As there are significant differences in methodologies developed by providers of ESG scores, we do not take the position that data from any single agency are to be favored. Consequently, we utilize ESG scores from Refinitiv in the manuscript’s empirical studies and redo all computations using S&P Global RobeoSAM ESG scores.

Keywords: ESG asset pricing; portfolio optimization; option pricing; reward–risk ratios; shadow riskless rate (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
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