Utilizing Neural Networks for Stocks Prices Prediction in Stocks Markets
Автор: Ahmed S. Mahedy, Abdelazeem A. Abdelsalam, Reham H. Mohamed, Ibrahim F. El-Nahry
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 3 Vol. 12, 2020 года.
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The neural networks, AI applications, are effective prediction methods. Therefore, in the current research a prediction system was proposed using these neural networks. It studied the technical share indices, viewing price not only as a function of time, but also as a function depending on several indices among which were the opening and closing, top and bottom trading session prices or trading volume. The above technical indices of a number of Egyptian stock market shares during the period from 2007 to 2017, which can be used for training the proposed system, were collected and used as follows: The data were divided into two sets. The first one contained 67% of the total data and was used for training neural networks and the second contained 33% and was used for testing the proposed system. The training set was segmented into subsets used for training a number of neural networks. The output of such networks was used for training another network hierarchically. The system was, then, tested using the rest of the data.
Backpropagation Neural Network, Egyptian stock market, Stock Prediction
Короткий адрес: https://sciup.org/15017449
IDR: 15017449 | DOI: 10.5815/ijitcs.2020.03.01
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