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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

Stock market prediction using LSTM

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  • Stock market prediction using LSTM

Yasmin Akter Bipasha 1, 2, *

1 College of Business, Westcliff University, Irvine, CA 92614, USA.
2 Bangladesh University of Professionals, Mirpur Cantonment, Dhaka-1216, Bangladesh.

Research Article

 

International Journal of Science and Research Archive, 2024, 12(02), 3146-3153.
Article DOI: 10.30574/ijsra.2024.12.2.1542
DOI url: https://doi.org/10.30574/ijsra.2024.12.2.1542

Received on 10 July 2024; revised on 22 August 2024; accepted on 28 August 2024

The stock market prediction patterns are seen as an important activity and it is more effective. Hence, stock prices will lead to lucrative profits from sound taking decisions. Because of the stagnant and noisy data, stock market-related forecasts are a major challenge for investors. Therefore, forecasting the stock market is a major challenge for investors to use their money to make more profit. This presents a stock market prediction based on Long Short-Term Memory (LSTM), designed to handle time series data and long-term dependencies. Historical stock price data for major technology companies, including Apple, Amazon, Google, and Microsoft, is collected from Yahoo Finance. The dataset contains key attributes such as open price, close price, high price, low price, and trading volume. These features are used to analyze stock behavior and predict future price movements. LSTM-based models can capture temporal relationships in stock market data more effectively than traditional statistical methods.

Stock market prediction; Long Short-Term Memory (LSTM); Time series analysis; Financial forecasting; Yahoo Finance data

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2024-1542.pdf

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Yasmin Akter Bipasha. Stock market prediction using LSTM. International Journal of Science and Research Archive, 2024, 12(02), 3146-3153. Article DOI: https://doi.org/10.30574/ijsra.2024.12.2.1542

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

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