STOCK MARKET PREDICTION USING MACHINE LEARNING

Abstract

With the prevalence of big data, deep learning has become an increasingly popular method for forecasting stock market trends and prices. We gathered two years of data from the Indian stock market and developed a deep learning model that incorporates a thorough approach to feature engineering in order to predict stock market price trends. Our approach includes a range of preprocessing techniques and multiple feature engineering methods, combined with a customized deep learning system specifically designed for predicting stock market price trends. We compared our proposed solution to frequently used machine learning models and found that our approach outperforms them due to the comprehensive feature engineering we employed. Our system achieves high levels of accuracy in predicting stock market trends. This work contributes to the research community by providing detailed information on prediction term lengths, feature engineering, and data preprocessing methods for stock analysis in both financial and technical domains.