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Massachusetts Institute of Technology

Testing for systematic ESG fund construction and independence measures

Abstract

dc:description.abstract

There has been significant research concerning the investment case for Environmental, Social and Governance Funds (ESG), however research into how these funds are constructed has been less studied. The purpose of this study is not to investigate the risk return case for ESG funds. Instead, this study will focus on the uniqueness of construction, and underlying assets of ESG specific funds. The majority of ESG classified investing is done through fund firms who self willingly vet their existing funds to ESG guidelines. It is more elocutionary, rather than a focused construction methodology. The hypothesis of this study is that funds created specifically for ESG investing are built on this same methodology, and are adapted from an existing fund very similar to the S&P 500. To test for uniqueness, large cap US equity ESG funds were compared against how many of the underlying assets were shared with the S&P 500. Signals found heavy overlap. However when looking at how the underlying assets are weighted in the fund verse the S&P 500, differences become more pronounced. Interestingly in the aggregate, the portion of the ESG funds dedicated to stocks that are not included in the S&P 500 were not that significant. There are several funds that are constructed with very different underlying assets than the S&P 500 Index, and funds that are very similar. This study then investigated how much of the underlying assets of each fund differed from the S&P 500 by adjusting the weights of just the underlying assets which it shares with each fund to measure the effect of dilution from the removed "non-ESG" compliant stocks. The resulting increase in overlap was significant for several individual funds, but modest for all funds. Then this study sampled to find if there is more overlap with different common index funds. Interestingly, there was often a higher overlap with the S&P 500 than with a fund's stated benchmark such as the Russell 1000 or Russell 1000 Value Index. Finally this study looked for correlations between the 3 month, 1 year, 3 year and Morningstar ESG peer performance percentiles. Modest correlations were found slightly favoring funds which were more similar to the S&P 500. Then correlations between each fund's management fee and similarity in the underlying assets were tested. There is evidence that the more unique the fund is, the higher the management fee. However, there is no evidence of correlation between the fund's management fee and the fund's Morningstar ESG score. The take away from this study is that some funds are very similar to index funds, like the S&P 500, while other funds have very little in common with standard index funds. There was significant overlap in the underlying assets and the S&P 500, however there was also significant differences in how the underlying assets were weighted. There was not a one to one exchange with a non-ESG compliant underlying asset with another asset with similar characteristic but was ESG compliant.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Engineering and Management Program
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gilmore, John Y
Advisor dc:contributor.advisor
  • Roberto Rigobon.

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/118551
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/118551

Chain of custody

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Base URL
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Last updated
2026-07-22
Source record
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citation

Gilmore, John Y. Testing for systematic ESG fund construction and independence measures. Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118551