Machine Learning Strategies for Understanding Stock Market Behaviour

Machine Learning Strategies for Understanding Stock Market Behaviour

Vivek Patil1, Samiksha Deshmukh2, Darshan Patil3, Vinay Mahajan4 , Dewanand Meshram5

1 Student, Department of I.T, RMD Sinhgad School of Engineering, Warje, Pune, Maharashtra, India

2 Student, Department of I.T, RMD Sinhgad School of Engineering, Warje, Pune, Maharashtra, India

3 Student, Department of I.T, RMD Sinhgad School of Engineering, Warje, Pune, Maharashtra, India

4 Student, Department of I.T, RMD Sinhgad School of Engineering, Warje, Pune, Maharashtra, India

5 Assistant Professor, Department of I.T, RMD Sinhgad School of Engineering, Warje, Pune, Maharashtra, India

Abstract: The stock market is a dynamic and complex financial system influenced by numerous factors, making accurate forecasting a challenging task. Traditional methods often fall short in capturing the intricate patterns within financial data. This research paper explores the application of machine learning techniques for stock market forecasting, aiming to provide a comprehensive overview of the current state of the field. The paper reviews relevant literature, discusses popular machine learning algorithms, and assesses their effectiveness in predicting stock market trends. Additionally, real-world applications and challenges in implementing machine learning for stock market forecasting are explored.