ESG framework and financial performance

: a principal component analysis and challenges for small investors in noise reduction

Abstract

This research proposes an effective way of reducing noise in Environmental Social and Governance (ESG) Scores, allowing small investors to quickly understand the impact of sustainability on financial performance. It starts with a comprehensive review of sustainability frameworks and the rise of ESG as a critical concept in today's literature. Specifically, I have denoted the importance of CSR models like Carroll's Pyramid, Triple Bottom Line Theory and Stakeholder Theory in explaining the current ESG framework. Afterwards, I analysed the connection between each ESG pillar and the ESG framework in finance. Mainly, I have explored the impact of sustainability in stock returns, denoting the incoherencies across different researchers and problems with the ESG Scores. By the end of the literature review, I have shown the challenges that small investors face when assessing ESG. To exploit noise in ESG, I have used a cross-section of the S&P 500 in 2022 with five different ESG scores: Bloomberg, Refinitive; Sustainalytics, Truvalue and FTSE Russell. The analysis have shown that different raters point to a different relation between ESG and stock returns; precisely, Truvalue and Sustainalytics both point to a negative outcome while the remaining point is a positive relation. To sort the situation and get a single relation, I have applied a principal component analysis (PCA) to reduce noise in the data, ending up with a positive relation between firms' financial and sustainable performance.

Date of Award	27 Oct 2023
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Paulo Alves (Supervisor) & Kim Kaivanto (Co-Supervisor)