1 publication

• Published Subscription Review Article 8 Sep 2025

  Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches

  By Nisar Shaikh, Pratik Hage, Jay Chakole, Krushnali Gulumkar, Purvesh Chaudhari

  Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …

  Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article →