Publications
Performance Attribution for Portfolio Constraints
2024We propose a new performance attribution framework that decomposes a constrained portfolio’s holdings, expected returns, variance, expected utility, and realized returns into components attributable to (1) the unconstrained mean-variance optimal portfolio; (2) individual static constraints; and (3) information, if any, arising from those constraints. A key contribution of our framework is the recognition that constraints may contain information that is correlated with returns, in which case imposing such constraints can affect performance. We extend our framework to accommodate estimation risk in portfolio construction using Bayesian portfolio analysis, which allows one to select constraints that improve—or are least detrimental to—future performance. We provide simulations and empirical examples involving constraints on environmental, social, and governance portfolios. Under certain scenarios, constraints may improve portfolio performance relative to a passive benchmark that does not account for the information contained in these constraints.
Quantifying the Returns of ESG Investing: An Empirical Analysis with Six ESG Metrics
2024Within the contemporary context of environmental, social, and governance (ESG) investing principles, the authors explore the risk–reward characteristics of portfolios in the United States, Europe, and Japan constructed using the foundational tenets of Markowitz’s modern portfolio theory with data from six major ESG rating agencies. They document statistically significant excess returns in ESG portfolios from 2014 to 2020 in the United States and Japan. They propose several statistical and voting-based methods to aggregate individual ESG ratings, the latter based on the theory of social choice. They find that aggregating individual ESG ratings improves portfolio performance. In addition, the authors find that a portfolio based on Treynor–Black weights further improves the performance of ESG portfolios. Overall, these results suggest that significant signals in ESG rating scores can enhance portfolio construction despite their noisy nature.
Optimal Impact Portfolios with General Dependence and Marginals
2024We develop a mathematical framework for constructing optimal impact portfolios and quantifying their financial performance by characterizing the returns of impact-ranked assets using induced order statistics and copulas. The distribution of induced order statistics can be represented by a mixture of order statistics and uniformly distributed random variables, where the mixture function is determined by the dependence structure between residual returns and impact factors—characterized by copulas—and the marginal distribution of residual returns. This representation theorem allows us to explicitly and efficiently compute optimal portfolio weights under any copula. This framework provides a systematic approach for constructing and quantifying the performance of optimal impact portfolios with arbitrary dependence structures and return distributions.
Quantifying the Impact of Impact Investing
2023We 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 bench-marks. 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.
A Brainier Approach to ESG Investing
2021Brains are the indispensable drivers of human progress, but brain health issues can wreak havoc on society. Consider the devastation of disorders like depression, anxiety, and Alzheimer disease—which cost the economy trillions each year. There are currently $40.5 trillion allocated to Environment, Sustainability, and Governance (ESG) investing around the world. If only a portion of these funds were diverted into brain health, they could produce major improvements for our society.
Funding Long Shots
2019We define long shots as investment projects with four features: (1) low probabilities of success; (2) long gestation lags before any cash flows are realized; (3) large required up-front investments; and (4) very large payoffs (relative to initial investment) in the unlikely event of success. Funding long shots is becoming increasingly difficult—even for high-risk investment vehicles like hedge funds and venture funds—despite the fact that some of society’s biggest challenges such as cancer, Alzheimer’s disease, global warming, and fossil-fuel depletion depend critically on the ability to undertake such investments. We investigate the possibility of improving financing for long shots by pooling them into a single portfolio that can be financed via securitized debt, and examine the conditions under which such funding mechanisms are likely to be effective.