SRI Strategies—Are there Trade-offs when Adding Impact Investing to a Quantitative Active Global Equity Portfolio?

The goal of this project was to assess the possible trade-offs of investment risk and return when adding Impact Investing factors to a quantitative active equity portfolio for the client, Gerstein Fisher, an investment management firm. The Capstone team first analyzed Environmental, Social, and Governance (ESG) datasets created by OWL Analytics and incorporated ESG data into a quantitative portfolio construction model through MSCI Barra Portfolio Manager (BPM), an industry standard portfolio analytics tool. Other helpful tools, such as the Agile Scrum methodology, Trello Board, Excel Macro, Python, and Tableau (a data visualization tool) were also used for this project.

The Capstone team constructed a set of portfolios separating Russell 3000 companies into quintiles according to their ESG scores. The companies in these portfolios were equally weighted, allowing the team to capture the full potential effect of a better ESG score on the risk or returns. The portfolios were further analyzed through a range of reports from BPM, including 5-year time series return attribution, risk and return, factor exposure, sectors (GICS) exposure, and risk attribution.

The team found that the best ESG scored companies have the best Sharpe Ratio while quintile three has the highest information ratio.  The research also found that the portfolio of firms with the best environmental and governance scores outperformed the benchmark portfolio in 4 years out of the past 5 years. Furthermore, the study showed that the top ESG performers generate the most active risk from Earnings Quality and Size, meaning that high ESG performers have better earnings quality and are usually larger. Additionally, financials sector constitutes the largest portion of the OWL data and has relatively high exposure in the low ESG quintiles. Moving forward,  it is highly possible to continue the research by conducting further back testing on those ESG portfolios. Tilting the portfolios towards more precise and granular characteristics, especially sub-rankings constituting the G and E scores could possibly generate higher expected return and limit risks.