New Events, Information Acquisition, and Serial Correlation

Prior research finds that momentum strategies (buying past losers and selling past winners) generate abnormal returns over medium-term (3- to 12-month) horizons. The Fama and French factors are unable to account for this effect, though they account for long-term reversals in asset returns. We develop a model which accounts for the medium-term continuation (momentum) 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