News Impact on Stock Trend

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Author(s)

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/ijeme.2019.06.05

Received: 15 Aug. 2019 / Revised: 25 Sep. 2019 / Accepted: 20 Oct. 2019 / Published: 8 Nov. 2019

Index Terms

Stock price movement, Financial News, ANN, CNN, LSTM, DSE

Abstract

Stock market trend can be predicted with the help of machine learning techniques. However, the stock market changes is uncertain. So it is very difficult and challenging to forecast stock price trend. The main goal of this paper is to implement a model for stock value trend prediction using share market news by machine learning techniques. Although this kind of work is implemented for the stock markets of various developed countries, it is not so common to observe such kind of analysis for the stock markets of underdeveloped countries. The model for this work is built on published stock data obtained from DSE (Dhaka Stock Exchange, Bangladesh), a representative stock market of an underdeveloped country. The empirical result reveals the effectiveness of Convolutional Neural Networks with LSTM model.

Cite This Paper

Protim Dey, Nadia Nahar, B M Mainul Hossain," News Impact on Stock Trend ", International Journal of Education and Management Engineering(IJEME), Vol.9, No.6, pp.40-49, 2019. DOI: 10.5815/ijeme.2019.06.05

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