Performance Attribution for Portfolio Constraints

Forthcoming in Management Science
Winner of the Commodity and Energy Markets Association (CEMA) Questrom-CEMA Best Paper Award
Winner of the CFRI&CIRF-China Finance Review International Research Excellence Award (Asset Management)

MIT Sloan School of Management Working Paper Series

91 Pages Posted: 1 Nov 2023 Last revised: 21 Oct 2024

See all articles by Andrew W. Lo

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering

Ruixun Zhang

Peking University; MIT Laboratory for Financial Engineering

Date Written: June 25, 2023

Abstract

We 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 ESG 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.

Keywords: Portfolio Theory, Performance Attribution, Constraints, Information, ESG Investing, Socially Responsible Investing JEL Classification: C10, G11, G12, Q56

JEL Classification: C10, G11, G12, Q56

Suggested Citation

Lo, Andrew W. and Zhang, Ruixun, Performance Attribution for Portfolio Constraints (June 25, 2023).
Forthcoming in Management Science
Winner of the Commodity and Energy Markets Association (CEMA) Questrom-CEMA Best Paper Award
Winner of the CFRI&CIRF-China Finance Review International Research Excellence Award (Asset Management)
, MIT Sloan School of Management Working Paper Series, Available at SSRN: https://ssrn.com/abstract=4609106 or http://dx.doi.org/10.2139/ssrn.4609106

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering ( email )

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Ruixun Zhang (Contact Author)

Peking University ( email )

5 Yiheyuan Road
Haidian District
Beijing, Beijing 100871
China

MIT Laboratory for Financial Engineering ( email )

100 Main Street
E62-611
Cambridge, MA 02142

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