The stock market operates through exchanges like the NSE and BSE, where trading takes place either in person or electronically. Stock prices constantly fluctuate based on supply and demand, which are influenced by a wide range of factors, including stock fundamentals, economic conditions, geopolitical events, and investors’ sentiments. Predicting stock prices accurately remains a major challenge as so many variables come into play. Ongoing research and advancements in Machine Learning (ML) and Artificial Intelligence (AI) are focused on making accurate stock prediction models which are s∂ more reliable and robust. This paper presents a comprehensive comparison of various AI and ML techniques used for stock market forecasting, highlighting their strengths, limitations, and practical applications. It aims to be a valuable resource for researchers, professionals, and investors who are looking to harness these technologies to make smarter financial decisions.
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Sehrawat et al. (2024) studied this question.