A STUDY ON STOCK MARKET RISK FORECASTING USING AI MODELS WITH REFERENCE TO GROWW

Abstract

The stock market is often unpredictable, making investment decisions difficult. The role of AI in enabling investors to handle uncertainty with increased assurance is explored in this paper. The research analyzes patterns in pricing history, trading behavior, and broad economic indicators using cutting-edge technology like deep learning and artificial intelligence. The research uses GROWW platform data to show how these insights are directly related to real investor actions and portfolio dangers. The objective is to assess how well AI can foretell both the near-term volatility of the market and the risks it may face in the future. Thorough evaluations are conducted on the identification of suitable qualities, data preparation, and real-time prediction. These endeavors enhance the models' accuracy, efficacy, and adaptability to evolving market circumstances. The results show that investing methods can be improved and losses can be decreased with the help of AI-driven forecasts. This requires simplifying complicated data so individual investors may make informed decisions.