Differences of Opinion, Information and the Timing of Trades

Abstract

This paper focuses on the impact that dispersion of opinions and asymmetric information have on turnover near releases of public information, using the probability of information-based trading (PIN) to proxy for information asymmetry and analysts' forecast dispersion for differences of opinion. For earnings announcements of US firms, I find that a one standard deviation increase in dispersion accelerates trading, reducing the difference between turnover around and before announcements by 8.50%. A similar increase in the PIN delays trading, raising the difference by 8.29%. These results help to explain why a large number of events have high turnover before earnings announcements relative to turnover after their release. Furthermore, the information contained in the time-series difference between trading around and before announcements helps to separate the impact of information asymmetry from the impact of proxies for differences of opinion. I also present a theoretical model in which agents who receive private information of heterogeneous quality trade a stock before and after observing a public signal. This public signal is interpreted differently across agents, leading to differences of opinion. I obtain closed-form solutions for expected aggregate volume and its derivatives with respect to these variables, showing that extending static models of asymmetric information is not enough to match the empirical findings.