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.
Bio:
Ruixun Zhang is an assistant professor and Boya Young Fellow in the Department of Financial Mathematics, School of Mathematical Sciences at Peking University (PKU). He is also affiliated with the PKU Center for Statistical Science, and the MIT Laboratory for Financial Engineering. Prior to joining PKU, Ruixun worked at several places including Google, Goldman Sachs, and a quant trading startup.
Ruixun received a PhD in applied mathematics from MIT in 2015, under the supervision of Andrew W. Lo. He received bachelor’s degrees in Mathematics and Applied Mathematics, and Economics (double degree) from Peking University in 2011. Ruixun’s research interests include evolutionary models of financial behavior, sustainable investing, FinTech, and various applications of machine learning.
