Stock Price Prediction Through the Sentimental Analysis of News Articles

Abstract

As people's interest in forecasting stock prices has been recently increased, research on stock price analysis through big data and artificial intelligence has been actively conducted. In this paper, we performed sentimental analysis by building and analyzing a sentimental dictionary with news articles. Through the sentimental dictionary, we can obtain the positive index of news articles for each date. By analyzing the correlation value between the positive index value and the stock return value, we can confirm the utility and possibility of the sentimental analysis in stock market.