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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 13, ISSUE 4, APRIL 2024

Stock Market Prediction Using Machine Learning

Jay Kadam, Jayesh Kasbe, Nachiket Nalawade, Abhinav Readdy, Prof. Trupti Sonkusare

DOI: 10.17148/IJARCCE.2024.13449
Abstract- This report extensively examines diverse methods for predicting stock market movements. It delves into three primary approaches: Fundamental Analysis, Technical Analysis, and the integration of Machine Learning techniques. Our findings align with the weak form of the Efficient Market Hypothesis, suggesting that historical prices alone might not hold significant predictive value, yet out-of-sample data could be indicative. We highlight the impact of relevant news on the fluctuations of stocks within listed companies, demonstrating its influence on market movements. Furthermore, our analysis underscores the potential utility of Fundamental Analysis and Machine Learning in assisting investors' decision-making processes. Keywords- Stock market prediction, Machine Learning, Efficient Market Hypothesis, Fundamental Analysis, Technical Analysis

How to Cite:

[1] Jay Kadam, Jayesh Kasbe, Nachiket Nalawade, Abhinav Readdy, Prof. Trupti Sonkusare, “Stock Market Prediction Using Machine Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2024.13449