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