文章基本信息

标题：Forecasting Stock Market Trend using Machine Learning Algorithms with Technical Indicators
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作者：Partho Protim Dey ; Nadia Nahar ; B M Mainul Hossain 等
期刊名称：International Journal of Information Technology and Computer Science
印刷版ISSN：2074-9007
电子版ISSN：2074-9015
出版年度：2020
卷号：12
期号：3
页码：32-38
DOI：10.5815/ijitcs.2020.03.05
出版社：MECS Publisher
摘要：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”.
关键词：Stock price movement;technical indicators;machine learning techniques;DSE