Employing Interval Grey Relational Analysis in ESG Investment Decision-Making Based on Ratings

Abstract

ESG ratings have gradually become an important reference basis in investment decisions. Currently, different rating agencies often give significant differences in ESG scores to the same enterprise based on their own assessment criteria, data sources, and weight settings. The inconsistent scores caused by such multi-source heterogeneous data increase the cognitive uncertainty and decision-making complexity of investors when utilizing ESG information, affecting the accuracy and reliability of investment judgments. In this paper, by introducing the Interval Number Grey Relational Analysis (IGRA) method, an enterprise investment ranking model based on multi-source ESG scores is constructed. The scores from different rating agencies are integrated into the form of interval numbers, effectively reflecting the fluctuation range of the scores. And with the help of the grey system theory, the similarity degree between enterprises and ideal reference objects is measured. Realize the comprehensive processing and scientific ranking of multi-dimensional uncertain information. An empirical analysis was conducted based on the ESG rating data to verify the effectiveness of the method. This research provides methods for ESG investment practices and also offers theoretical references for dealing with uncertain investment issues.