Role of Environmental, Social and Governance on Firm Value using Support Vector Machine

Environmental, Social, and Governance (ESG) aspects of company value are attracting more and more attention among legislators, stakeholders, and investors. ESG criteria provide a full assessment of a company’s ethical behaviour and long-term viability, therefore influencing its financial performance, risk profile, and reputation. The study spans ten years (2013-2023) using a 500 -company dataset spanning a spectrum of industries. Apart from traditional financial benchmarks including market-to-book ratio, return on assets (ROA), and return on equity (ROE), input variables comprise ESG ratings. By means of a radial basis function (RBF) kernel, training the SVM model helps to capture the non-linear relationships between business value and ESG performance. Cross-valuation guarantees model robustness; hyperparameter adjustment maximizes the correctness of the model. Business value and ESG scores demonstrate a statistically significant positive link. Forecasting company value, the SVM model gets an accuracy of 87.5%, a precision of 85.2%, a recall of 88.4%, and an F1 score of 86.8%. Higher ESG score businesses have a 12% larger market-to-book ratio than those with lower scores, suggesting that ESG performance helps to explain corporate valuation. The findings demonstrate their ability to increase corporate value and provide empirical evidence supporting the inclusion of ESG factors into investment decisions-making processes.