Authors - Sneha Warrier, Umesh Mahtani, Smitha Rao Abstract - This study makes a novel attempt using ensemble Machine Learning (ML) techniques to analyze the impact of various Environmental, Social, and Governance (ESG) indicators on the financial performance of publicly listed entities in India. The findings highlight the importance of looking beyond the ESG score and assessing the most important ESG indicators that impact firms’ finan-cial performance. The main findings establish a relationship between Tobin’s Q (firm value) and individual ESG indicators. The study shows that ESG indicators have comparatively less impact on the internal accounting measures of Return on Total Assets (ROA) and Return on Net Worth (RONW). The results list the following key ESG indicators: energy intensity and consumption, equal and mini-mum wages to employees, turnover rate, as those having impact on Tobin’s Q across the various ML models explored. These research findings would assist corporations, investors, and policymakers in identifying key ESG indicators that impact financial performance of companies.
