Forecasting Stock Market Trend using Machine Learning Algorithms with Technical Indicators | Zendy

Partho Protim Dey | Zendy; Nadia Nahar | Zendy; B M Mainul Hossain | Zendy

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Forecasting Stock Market Trend using Machine Learning Algorithms with Technical Indicators

Author(s) -

Partho Protim Dey,

Nadia Nahar,

B M Mainul Hossain

Publication year - 2020

Publication title -

international journal of information technology and computer science

Language(s) - English

Resource type - Journals

eISSN - 2074-9015

pISSN - 2074-9007

DOI - 10.5815/ijitcs.2020.03.05

Subject(s) - computer science , stock market , stock exchange , stock (firearms) , machine learning , artificial intelligence , technical analysis , algorithm , econometrics , finance , economics , mechanical engineering , paleontology , horse , engineering , biology

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”.

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