Abstract

This paper uses two techniques to build a socially responsible portfolio of U.S. equities and examines prospective performance using publicly available data. The first technique eliminates stocks from consideration using categorical exclusions with a restrictive Environment, Social and Governance screen. The paper shows that stocks surviving the screen have a significantly higher average projected Value Line alpha and are more likely to have a Morningstar 5-star rating. Using categorical exclusions, however, introduces a sector bias in that the ESG screen is more likely to restrict stocks from the manufacturing sector than the service sector. The second technique does not introduce a sector bias because it uses a best-in-class optimization approach in place of screening. The paper introduces a linear programming model called Data Envelopment Analysis to the application of SRI portfolio development to find the best financially and socially performing companies within each industry sector. When compared to a categorical exclusions portfolio, a DEA portfolio is rated significantly higher by Morningstar and Value Line. Depending on the specific needs of a socially responsible investor, the DEA technique could be a better tool in developing a financially and socially balanced equity portfolio.