The Development of a Deep Learning Model for Predicting Stock Prices

Authors

  • Rusul Mansoor Al-Amri College of Nursing, University of Al-Ameed, Karbala, PO No: 198, Iraq
  • Ahmed Adnan Hadi Computer Techniques Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, Babil, Iraq
  • Ayad Hameed Mousa College of Computer Science and Information Technology, University of Kerbala, Kerbala, Iraq
  • Hasanain Flayyih Hasan College of Computer Science and Information Technology, University of Wasit, Wasit, Iraq
  • Mayameen S. Kadhim Department of Medical Instruments Techniques Engineering, Technical College of Engineering, Albanyan University, Baghdad, Iraq

DOI:

https://doi.org/10.37934/araset.31.3.208219

Keywords:

Stock price, Sentiment Analysis, Deep learning, BiLSTM

Abstract

The volatility and complexity of the stock market make it difficult to predict stock values accurately. The primary goal of this paper is to overcome some of these difficulties by training the data to anticipate stock prices based on sentiment analysis of tweets. Using natural language processing (NLP) technology, the tweet sentiments were categorized into (positive - neutral - negative). The stock price was predicted using deep learning algorithms (CNNs, RNNs, LSTMs, BiLSTMs). Among the algorithms, (BiLSTM) achieved the best results in terms of accuracy (94%) and the others (CNN=90%, RNN=91%, LSTM=92%). The paper also confirms that the average MSE and RMSE (MSE=0.03552, RMSE=0.1882064) for the BiLSTM algorithm are achieved (MSE=0.03552, RMSE=0.1882064). As a result, the obtained results were better than previous studies.

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Author Biographies

Rusul Mansoor Al-Amri, College of Nursing, University of Al-Ameed, Karbala, PO No: 198, Iraq

ru.al-amri@alameed.edu.iq

Ahmed Adnan Hadi, Computer Techniques Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, Babil, Iraq

aarhrf@gmail.com

Ayad Hameed Mousa, College of Computer Science and Information Technology, University of Kerbala, Kerbala, Iraq

ayad.h@uokerbala.edu.iq

Hasanain Flayyih Hasan, College of Computer Science and Information Technology, University of Wasit, Wasit, Iraq

Hasaneen.hfhm@outlook.com

Mayameen S. Kadhim, Department of Medical Instruments Techniques Engineering, Technical College of Engineering, Albanyan University, Baghdad, Iraq

Mayameen.s@albayan.edu.iq

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Published

2023-08-14

How to Cite

Rusul Mansoor Al-Amri, Ahmed Adnan Hadi, Ayad Hameed Mousa, Hasanain Flayyih Hasan, & Mayameen S. Kadhim. (2023). The Development of a Deep Learning Model for Predicting Stock Prices. Journal of Advanced Research in Applied Sciences and Engineering Technology, 31(3), 208–219. https://doi.org/10.37934/araset.31.3.208219

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Articles