Machine Learning and The Future of Stock Market Analysis in Investment Planning
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Dr R. Poorvadevi1, Bhavana Priya Chalamcharla2, Davu Manasa3
1Assistant Professor, Department of CSE, SCSVMV University. Email: poorvadevi@gmail.com
2Department of CSE, SCSVMV University, Kanchiuram, Tamil Nadu, India. Email: priyasharma98533@gmail.com
3Department of CSE, SCSVMV University, Kanchiuram, Tamil Nadu, India. Email: davumanasa004@gmail.com
Abstract
The stock market, characterized by its volatility and a wide array of influencing factors, presents challenges for investors seeking to predict market trends and make sound decisions. This research delves into the application of machine learning in enhancing stock market forecasting. We explore how advanced algorithms, such as deep learning models and multiple regression techniques, provide superior insights compared to conventional prediction methods. Our analysis shows that machine learning can improve the accuracy and reliability of stock price forecasts, giving investors the tools to make more strategic and data-driven decisions. The findings highlight the transformative potential of these technologies in reshaping investment methodologies and providing a competitive advantage in the financial market.
Keywords
Machine Learning, Stock Forecasting, Deep Learning, Regression Techniques, Investment Decision-Making
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