Evaluating Retail Investor Responses to AI-Based Trading Tools in Chennai's Stock Market

Stock dealers in Chennai use traditional trading systems. These systems require users to make decisions and use simple technological indications. It also results in up-and-down investing results influenced by emotions and personal beliefs. These systems attempt to make sense of complicated data and keep up with market sentiment in real time, limiting their effectiveness. To address these issues, the proposed system leverages advanced machine learning techniques such as reinforcement learning (RL) and natural language processing (NLP) to provide real-time, data-driven trading advise. The RL technique improves trading strategies by trial and error, whereas sentiment analysis assesses market mood using various text sources. The results reveal that the new system has a 20% ROI and a Sharpe ratio of 1.3, outperforming traditional methods. It also has lower maximum decreases, indicating that it manages risk better. The AI-driven strategy not only helps stock traders make more accurate decisions, but it also gives them tools to better manage their investments and assess risk in a volatile market.