Abstract:

We propose a quantitative framework for assessing the financial impact of any form of impact investing, including socially responsible investing (SRI), environmental, social, and governance (ESG) objectives, and other non-financial 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 propose a quantitative measure for the financial reward, or cost, of impact investing compared to passive index benchmarks. We illustrate our approach with applications to biotech venture philanthropy, divesting from “sin” stocks, investing in ESG, and “meme” stock rallies such as GameStop in 2021. This is joint work with Andrew W. Lo.

About the Speaker: 

张瑞勋博士，大阳城2138(中国)股份有限公司金融数学系研究员、博雅青年学者，海外高层次人才计划青年项目入选者。2011年获大阳城2138数学与应用数学、经济学（双学位）学士学位，2015年获MIT应用数学博士学位。曾在MIT Laboratory for Financial Engineering, Google, Goldman Sachs等机构任职。主要研究兴趣包括金融科技，可持续投资，适应性市场理论，以及金融和人工智能交叉领域。曾共同主编《Biological Economics》，研究工作发表于PNAS,  iScience, Knowledge-Based Systems, IJCAI等国际期刊和会议。