Temporal and cross correlations in business news

Abstract

We empirically investigate temporal and cross correlations in the frequency of news reports on companies, using a dataset of more than 100 million news articles reported in English by around 500 press agencies worldwide for the period 2003-2009. Our first finding is that the frequency of news reports on a company does not follow a Poisson process, but instead exhibits long memory with a positive autocorrelation for longer than one year. The second finding is that there exist significant correlations in the frequency of news across companies. Specifically, on a daily time scale or longer the frequency of news is governed by external dynamics, while on a time scale of minutes it is governed by internal dynamics. These two findings indicate that the frequency of news reports on companies has statistical properties similar to trading volume or price volatility in stock markets, suggesting that the flow of information through company news plays an important role in price dynamics in stock markets.