Abstract: The stock market is a complex, dynamic system influenced by economic indicators, political factors, and investor sentiment. Predicting its behavior has been a long-standing challenge due to its nonlinear and volatile nature. Recent advancements in Machine Learning (ML) and Deep Learning (DL) have enabled researchers to develop more robust and adaptive models for stock market prediction. This paper provides a comprehensive review of various ML and DL techniques, their comparative performance, challenges, and future directions in financial forecasting.
Keywords: Stock Market Prediction, Machine Learning, Deep Learning, LSTM, ARIMA, Sentiment Analysis
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DOI:
10.17148/ Edit IJARCCE.2025.141158
[1] Jadhav Sandesh, Pawar Satpal, Phadtare Kshitija, Hadwale Dattatray, Dr. Taware. G. G, Mr. A.S. Bhapkar, "Stock Market Prediction Using Machine Learning and Deep Learning Techniques," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/ Edit IJARCCE.2025.141158
