Forecasting Stock Market Trend using Machine Learning Algorithms with Technical Indicators
Автор: Partho Protim Dey, Nadia Nahar, B. M. Mainul Hossain
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 3 Vol. 12, 2020 года.
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Stock market prediction is a process of trying to decide the stock trends based on the analysis of historical data. However, the stock market is subject to rapid changes. It is very difficult to predict because of its dynamic & unpredictable nature. The main goal of this paper is to present a model that can predict stock market trend. The model is implemented with the help of machine learning algorithms using eleven technical indicators. The model is trained and tested by the published stock data obtained from DSE (Dhaka Stock Exchange, Bangladesh). The empirical result reveals the effectiveness of machine learning techniques with a maximum accuracy of 86.67%, 64.13% and 69.21% for “today”, “tomorrow” and “day_after_tomorrow”.
Stock price movement, technical indicators, machine learning techniques, DSE
Короткий адрес: https://sciup.org/15017453
IDR: 15017453 | DOI: 10.5815/ijitcs.2020.03.05
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