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Nature of Computation and Communication. 7th EAI International Conference, ICTCC 2021, Virtual Event, October 28–29, 2021, Proceedings

Research Article

Predicting Vietnamese Stock Market Using the Variants of LSTM Architecture

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  • @INPROCEEDINGS{10.1007/978-3-030-92942-8_11,
        author={Cong-Doan Truong and Duc-Quynh Tran and Van-Dinh Nguyen and Huu-Tam Tran and Tien-Duy Hoang},
        title={Predicting Vietnamese Stock Market Using the Variants of LSTM Architecture},
        proceedings={Nature of Computation and Communication. 7th EAI International Conference, ICTCC 2021, Virtual Event, October 28--29, 2021, Proceedings},
        proceedings_a={ICTCC},
        year={2022},
        month={1},
        keywords={LSTM Bidirectional LSTM VN-INDEX Stock market prediction},
        doi={10.1007/978-3-030-92942-8_11}
    }
    
  • Cong-Doan Truong
    Duc-Quynh Tran
    Van-Dinh Nguyen
    Huu-Tam Tran
    Tien-Duy Hoang
    Year: 2022
    Predicting Vietnamese Stock Market Using the Variants of LSTM Architecture
    ICTCC
    Springer
    DOI: 10.1007/978-3-030-92942-8_11
Cong-Doan Truong1,*, Duc-Quynh Tran1, Van-Dinh Nguyen1, Huu-Tam Tran2, Tien-Duy Hoang
  • 1: International School
  • 2: Faculty of Information Technology
*Contact email: doantc@isvnu.vn

Abstract

Recently, the problem of stock market prediction has attracted a lot of attention. Many studies have been proposed to apply to the problem of stock market prediction. However, achieving good results in prediction is still a challenge in research and there are very few studies applied to Vietnamese stock market data. Therefore, it is necessary to improve or introduce new forms of prediction. Specifically, we have focused on the stock prediction problem for the Vietnamese market in the short and long term. Long short-term memory (LSTM) based on deep learning model has been applied to big data problem such as VN-INDEX. We compared the prediction results of the variants of the LSTM model with each other. The results obtained are very interesting that the Bidirectional LSTM architecture gives good results in short- and long-term prediction for the Vietnamese stock market. In conclusion, the LSTM architecture is very suitable for the stock prediction problem in the long- and short- term.

Keywords
LSTM Bidirectional LSTM VN-INDEX Stock market prediction
Published
2022-01-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-92942-8_11
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