Estimating the Intensity of News Based on Trade Data

This paper investigates the problem of identifying the strength of the incoming of news in the financial market. With the support of a microstructure model we are able to derive a simple formula that, based only on trade data, estimates the likelihood of having news for any given tradable asset in a particular time period. The formula can be easily implemented and takes just one input, the probability of a zero trade price difference conditional on the incoming of consecutive same sign trades. In the empirical part of the paper we investigate the properties of this proposed estimator of news intensity for twenty stocks from the Brazilian equity market, covering two full years from 2010 to 2012. The results are very encouraging and consistent across assets. First we find that the strength of news have a common component across all assets. We attribute that to the fact that the incoming of new information regarding the Brazilian economy will affect all stocks. We also see that the likelihood of news is strongly and positively related to volatility of price differences and negatively related to trade volume. The first can be explained by the fact that volatility is a bi-product of news and the second by the presence of traders avoiding the disclosure of private information by trading smaller volumes. In the empirical section we are also able to show that the intensity of news has a intraday pattern, with higher values at the beginning of the trading day and lower values at the end. This result is consistent with the view that the beginning of the trading day is the time when accumulated overnight information reaches the market, therefore increasing news intensity.