News Events, Information Acquisition, and Serial Correlation

We develop a model that accounts for medium-term continuation (momentum) in asset returns by analyzing information acquisition about news events (such as earnings announcements) in a multiperiod setting. As more and more agents become informed about news events, temporal uncertainty is resolved endogenously through market prices over time, which leads to positive autocorrelations in asset returns. We empirically estimate serial correlations over medium-term horizons for portfolios sorted by firm size and past stock performance and find that calibration of serial correlations in our model spans the range of empirically estimated correlations