Application of Deep Learning in Predicting ESG Index Volatility

As achieving the "dual carbon" goals becomes increasingly important, environmental, social, and governance (ESG) information transparency has become a core factor affecting the entire capital market. Society's attention to ESG information is gradually increasing. If enterprises want to achieve higher economic benefits, they need to continuously optimize their ESG performance. Based on this, how to use artificial intelligence (AI) technology to predict the volatility of ESG indices is a question that we need to consider carefully. This article proposes a deep learning (DL) model to predict the volatility of ESG indices. The model can deeply analyze diverse ESG data, accurately capture the dynamic trends of ESG indices, and provide data-driven decision-making assistance for investors. At the same time, our model can also help companies identify hidden risks in ESG management. The experimental results show that our model accurately predicts ESG index volatility.