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What is Machine Learning for ESG Rating Estimation about?

This paper explores the use of machine learning, specifically a Random Forest classification model, to estimate ESG ratings based on balance sheet ratios and systemic risk for EuroStoxx 600 firms from 2016 to 2021. It highlights the importance of ESG ratings in investment decisions and their correlation with corporate financial performance, while addressing the challenges of methodological inconsistencies and data quality. The findings suggest that this approach could enhance the accuracy of ESG rating esti

Author

Thảo Lê

Language

EN