Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India

Research Article

Stock Market Prediction using LSTM

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  • @INPROCEEDINGS{10.4108/eai.27-2-2020.2303545,
        author={Priya  Sidhu and Himanshu  Aggarwal and Madan  Lal},
        title={Stock Market Prediction using LSTM},
        proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India},
        publisher={EAI},
        proceedings_a={ICIDSSD},
        year={2021},
        month={3},
        keywords={stock price lstm methodology},
        doi={10.4108/eai.27-2-2020.2303545}
    }
    
  • Priya Sidhu
    Himanshu Aggarwal
    Madan Lal
    Year: 2021
    Stock Market Prediction using LSTM
    ICIDSSD
    EAI
    DOI: 10.4108/eai.27-2-2020.2303545
Priya Sidhu1,*, Himanshu Aggarwal1, Madan Lal1
  • 1: Dept.of Computer Science& Engineering, Punjabi University, Patiala
*Contact email: sidhupriyaa@gmail.com

Abstract

In this paper, the analyses of stock is done using Long-Short-Term Memory as it helps in predicting the future price of the stock market. LSTM focuses on predicting the next output that will help to do the time series analysis. Therefore, to do the forecasting of the stock price, we have to consider the closing price. LSTM helps to find the future price using the previous day’s closing price. LSTM neural network helps in predicting TATAGLOBAL stock by using multi-feature input variables to verify the prediction effect on the stock time series.