Partho Protim Dey; Nadia Nahar; B M Mainul Hossain

Forecasting Stock Market Trend using Machine Learning Algorithms with Technical Indicators

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Author(s)

Partho Protim Dey ^1,* Nadia Nahar ¹ B M Mainul Hossain ¹

1. Institute of Information Technology, University of Dhaka, Dhaka 1000, Bangladesh

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2020.03.05

Received: 9 Dec. 2019 / Revised: 1 Feb. 2020 / Accepted: 14 Feb. 2020 / Published: 8 Jun. 2020

Index Terms

Stock price movement, technical indicators, machine learning techniques, DSE

Abstract

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”.

Cite This Paper

Partho Protim Dey, Nadia Nahar, B M Mainul Hossain, "Forecasting Stock Market Trend using Machine Learning Algorithms with Technical Indicators", International Journal of Information Technology and Computer Science(IJITCS), Vol.12, No.3, pp.32-38, 2020. DOI:10.5815/ijitcs.2020.03.05

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International Journal of Information Technology and Computer Science (IJITCS)