Title :
Extracting News Sentiment and Establishing Its Relationship with the S&P 500 Index
Author :
Zubair, Sahil ; Cios, Krzysztof J.
Author_Institution :
Dept. of Comput. Sci., Virginia Commonwealth Univ., Richmond, VA, USA
Abstract :
Sentiment analysis has been shown to be a useful tool for quantitative analysis in the world of finance. Researchers have shown that the sentiment picked up from the news media can be correlated with movement of the stock market. Here we use the Harvard General Inquirer to determine the sentiment present in Reuter´s articles. After first generating positive and negative sentiment data we use the Kalman filter for smoothing. We then establish a correlation between the movement of the S&P 500 and sentiment. The results indicate that correlations between the sentiment in the news and the S&P index are strong for five of the seven years analyzed.
Keywords :
Kalman filters; correlation methods; data mining; smoothing methods; stock markets; time series; Harvard General Inquirer; Kalman filter; Reuter articles; S&P 500 index; correlations; finance world; negative sentiment data; news media; news sentiment analysis; news sentiment extraction; opinion mining; positive sentiment data; quantitative analysis; smoothing; stock market movement; time series; Correlation coefficient; Economics; Indexes; Kalman filters; Sentiment analysis; Time series analysis; Vectors;
Conference_Titel :
System Sciences (HICSS), 2015 48th Hawaii International Conference on
Conference_Location :
Kauai, HI
DOI :
10.1109/HICSS.2015.120