A STUDY ON ROLE OF AI IN STOCK MARKET PREDICTION WITH SPECIAL REFERENCE TO COIMBATORE CITY

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This study examines the role of Artificial Intelligence (AI) in improving stock market prediction and investment decision-making. Stock market forecasting has always been challenging due to the influence of multiple economic, financial, and behavioural factors. Traditional prediction methods often struggle to analyse large volumes of financial data and complex market patterns. With the advancement of technology, Artificial Intelligence has emerged as a powerful tool that can process massive datasets, identify hidden patterns, and generate more accurate predictions. The study aims to understand the concept of AI and analyse how AI techniques contribute to predicting stock price movements. Various AI approaches such as machine learning, deep learning, neural networks, and algorithmic trading systems are examined to understand their application in financial markets. The research also compares AI-based prediction methods with traditional forecasting techniques to evaluate their effectiveness. In addition, the study explores how AI reduces human errors and emotional bias in investment analysis. The findings indicate that AI technologies help investors interpret market trends more efficiently and support data-driven decision-making. Although AI offers several benefits such as speed, automation, and improved accuracy, it also faces challenges including data dependency and market uncertainty. Overall, the study highlights the growing importance of AI in modern financial markets and its potential to transform stock market analysis and forecasting.

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