This study investigates the influence of the U.S. Energy Independence and Security Act (EISA) of 2022 on stock market volatility. Considering potential policy impacts on market dynamics, it employs a mean-reverting jump-diffusion model for volatility analysis, supported by rigorous hypothesis testing to validate empirical findings. For investor sentiment analysis, a pre-trained model (BERT-base-multilingual-uncased) is used to assess sentiment, with logistic regression and Bidirectional LSTM utilized for sentiment prediction. Contrary to conventional findings, logistic regression outperforms Bidirectional LSTM for the small dataset. Overall, the study estimates show no statistically noteworthy difference in volatility before and after implementing the EISA of 2022. This study provides valuable insights for navigating financial decisions within the intricate landscape of energy markets.