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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 12, ISSUE 5, MAY 2023

Stock Market Prediction Using RNN

Avin Mahajan, Krushna Fuke, Shivam Raut, Pranay Mahakal, Prof. Zarina Shaikh

DOI: 10.17148/IJARCCE.2023.125219

Abstract: Future stock prices are frequently predicted using historical financial entity prices. This paper uses a two-layer reasoning technique to present a novel financial entity price prediction model. The first layer directs the second layer, which relies on learning techniques, using domain knowledge acquired from scientific study.An effective money management approach is added to the model to increase its performance. When choosing whether to buy, sell, or do nothing, this method takes into account the past performance of the model's predictions as well as the investor's available funds. The development of deep learning mining, which seeks to identify profitable technical trading patterns made up of combinations of indicators taken from previous financial data series, distinguishes this work from others. Trading guidelines are regarded as these patterns.

Keywords: Stock Market, RNN.

How to Cite:

[1] Avin Mahajan, Krushna Fuke, Shivam Raut, Pranay Mahakal, Prof. Zarina Shaikh, “Stock Market Prediction Using RNN,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.125219