Quantifying the Impact of Impact Investing

Andrew W. Lo () and Ruixun Zhang ()
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Andrew W. Lo: MIT Sloan School of Management, MIT Laboratory for Financial Engineering, MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts 02142; Santa Fe Institute, Santa Fe, New Mexico 87501
Ruixun Zhang: Peking University School of Mathematical Sciences, Peking University National Engineering Laboratory for Big Data Analysis and Applications, Peking University Center for Statistical Science, Peking University Laboratory for Mathematical Economics and Quantitative Finance, Beijing 100871, China

Management Science, 2024, vol. 70, issue 10, 7161-7186

Abstract: We propose a quantitative framework for assessing the financial impact of any form of impact investing, including socially responsible investing; environmental, social, and governance (ESG) objectives; and other nonfinancial investment criteria. We derive conditions under which impact investing detracts from, improves on, or is neutral to the performance of traditional mean-variance optimal portfolios, which depends on whether the correlations between the impact factor and unobserved excess returns are negative, positive, or zero, respectively. Using Treynor–Black portfolios to maximize the risk-adjusted returns of impact portfolios, we derive an explicit and easily computable measure of the financial reward or cost of impact investing as compared with passive index benchmarks. We illustrate our approach with applications to biotech venture philanthropy, a semiconductor research and development consortium, divesting from “sin” stocks, ESG investments, and “meme” stock rallies such as GameStop in 2021.

Keywords: impact investing; environmental; social; and governance (ESG) investing; socially responsible investing; venture philanthropy; investments (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:70:y:2024:i:10:p:7161-7186

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