The Drivers of ESG Index Outperformance : A Transatlantic Analysis of US and European Markets

The purpose of this study is to meticulously investigate the varying effects of diverse Environmental, Social, and Governance (ESG) integration approaches on the financial performance of securities within the European and US markets over the decade from 2013 to 2023. This research topic represents a valuable contribution to the existing literature, which it provides a more nuanced perspective on how ESG considerations should be intricately woven into the fabric of investment decision-making processes, serving as an actionable playbook for investors of ESG-related goals. The study exhaustively examines over 200 portfolio simulations, utilizing a comprehensive selection of 22 equity and bond indexes spanning both European and US markets. The findings reveal that a 'best-in-class', sector-relative selection approach based on ESG ratings typically outperforms in Europe. Conversely, an 'optimization-focused' approach that leans towards market-cap weighting based on ESG scores delivers superior performance in the US. A range of factors that potentially influence these differential outcomes are explored in depth. These include the unique regulatory environments across regions, the dynamic nature of markets, the varying preferences of investors, and the distinct sector compositions inherent to each region. Furthermore, the research acknowledges the pivotal role those emergent technologies, such as big data and artificial intelligence (AI), are playing in shifting the global investment landscape towards sustainable practices. To provide a future-oriented perspective, the study incorporates several practical applications of AI technology in the domain of ESG investing. These insights not only demonstrate the transformative potential of AI but also underscore the importance of technological adaptation in achieving sustainable investment outcomes.

Name thesis:degree_name

Master

Department dc:contributor.department

Sloan School of Management

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Chen, Jinlan (Iris)

Advisor dc:contributor.advisor

• Johnson, Simon

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/151576

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151576