Investigating Timing and Impact of News on the Stock Market

Abstract

Predicting stock market movements is an interesting and challenging problem: researchers and traders have approached this task with different techniques, from time series prediction to technical and fundamental analysis. Nowadays, a huge amount of textual data can be used to lead a new source of information on this task, well known to be highly stochastic and temporal dependent. In this paper, we investigate the problem of analyzing the timing and the impact that news have on the stock market. We focus on two different important aspects: the possible contribution that new information can have on the stock price and its possible relation with the aggregate news recently published. Our approach involves using the information available now to predict different prices movements, from the recent past to the far future. Results on US market show that the information contained in news can be used as an accurate predictor for past price movements. When the future is considered, however, the correlation between news and stock market becomes less clear.