JOURNAL ARTICLE
Correlation Study between Returns and ESG Ratings.
Published In: Journal of Impact & ESG Investing, 2024, v. 5, n. 1. P. 98 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Cazaux, Hugo; Rudd, Ralph; Stefánsson, Hlynur; Ólafsson, Sverrir; Raberto, Marco; Ásgeirsson, Eyjólfur Ingi 3 of 3
Abstract
ESG ratings have become a central topic in finance amid global initiatives for sustainability. This study examines the relationship between ESG ratings and log returns through Pearson's correlation coefficient, offering a granular analysis across various sectors and pinpointing specific materiality issues as defined by the Sustainability Accounting Standards Board (SASB). The article uncovers empirical evidence that demonstrates a spectrum of negative to positive correlations, which are dependent on the sector in question and the relevant materiality issues. The study delves into the potential repercussions of such correlations, considering the perspectives of both corporations and investors. It underscores how positive correlations might incentivize companies to enhance their ESG ratings, whereas negative correlations could signal to investors considerations to take into account in their investment strategies. The research also illuminates the pivotal role that SASB-defined materiality issues play in refining the understanding of ESG's impact on financial performance, suggesting that a nuanced approach to ESG investment could be beneficial. The study contributes to a deeper comprehension of how ESG factors are a valuable signal with financial outcomes, which could guide future corporate strategies and investment decisions toward sustainable growth. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Impact & ESG Investing. 2024/09, Vol. 5, Issue 1, p98
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2024
- ISSN:2693-1982
- DOI:10.3905/jesg.2024.1.104
- Accession Number:179688921
- Copyright Statement:Copyright of Journal of Impact & ESG Investing is the property of With Intelligence Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.