Title: Stock price forecasting and news sentiment analysis model using artificial neural network

Authors: Somesh Yadav; Ritesh Singh Suhag; K.V. Sriram

Addresses: Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India ' Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India ' Department of Humanities and Management, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka 576104, India

Abstract: The stock market is highly volatile, and the prediction of stock prices has always been an area of interest to many statisticians and researchers. This study is an attempt to predict the prices of stock using artificial neural network (ANN). Three models have been built, one for the future prediction of stock prices based on previous trends, the second for prediction of next day closing price based on today's opening price, and the third one analyses the sentiment of news articles and gives scores based on the news impact. ANN is trained with the historical data using R-studio platform which is then used to predict the future values. Our experimental results for various stock prices showed that the model is effective using ANN.

Keywords: stock price; forecasting; artificial neural network; ANN; sentiment analysis; opening price; closing price; R-studio; data analytics.

DOI: 10.1504/IJBIDM.2021.115967

International Journal of Business Intelligence and Data Mining, 2021 Vol.19 No.1, pp.113 - 133

Received: 29 Jun 2018
Accepted: 17 May 2019

Published online: 11 Jun 2021 *

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