Clustering stocks by ESG criteria: financial performance implications

This research provides a comprehensive analysis of the Environmental, Social, and Governance scores of the Eurostoxx index constituents from 2007 to 2023. Initially, the study delves into the annual ESG score trends, exploring the underlying patterns and variations in ESG performance over different years. Subsequently, we employ clustering techniques to categorize stocks based on their ESG profiles, utilizing both simple quantile-based clustering method and the K-means algorithm. The primary objectives of this analysis are first, to try to identify distinct groups of stocks with similar ESG characteristics, and second, to assess the impact of these ESG-based clusters on financial performance. The clustering analysis facilitates the identification of homogeneous groups of stocks that exhibit similar behaviors in their ESG scores, providing insights into how environmental, social, and governance practices correlate with each other within the index. In the second phase of the study, we investigate the relationship between the identified ESG clusters and stock returns. This includes evaluating the financial performance of portfolios formed based on these clusters and analyzing their risk-adjusted returns, the performance assessment is carried out using metrics such as excess returns, yearly, and a 3-year period performance, standard deviation, and the Sharpe ratio. The findings of this report can have significant implications for investors and asset managers seeking to integrate ESG criteria into their investment strategies. By demonstrating the relationship between ESG practices and financial performance, this study provides empirical evidence analyzing the adoption of sustainable investment practices with long-term profitability and risk management goals.