Abstract
The forecasting of the stock exchange asking price has been affected by a number of monetary and nonmanetary indexes that might be used as a warning rule for investors. Expecting the future trend of the stock market is a critical issue in investment sector. In this work, the forecasting of futurity open and close asking price of Dow Jones Industrial Average (DJIV) has been performed utilization deep neural network. The Long short term memory (LSTM) network was used to predict values of futurity time steps of a sequence of opening and closing into Dow Jones Industrial Average stock market. The LSTM network learns to forecast the value of the next step. By train the LSTM network, we have expect the value of future time steps of open and close of the stock market. The performance of the proposed technique is promising for DJIV stock market expectation.
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Al-Shayea, Q. (2022). Deep Neural Network to Forecast Stock Market Price. In: Yaseen, S.G. (eds) Digital Economy, Business Analytics, and Big Data Analytics Applications. Studies in Computational Intelligence, vol 1010. Springer, Cham. https://doi.org/10.1007/978-3-031-05258-3_12
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DOI: https://doi.org/10.1007/978-3-031-05258-3_12
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