We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Momentum arises from the investor gradually learning about the relative accuracy of the information sources and updating their weights. Empirical tests validate the model's prediction of stronger momentum in stocks with large information weight fluctuations and high forecast dispersion. We also identify return predictability attributable to changes in the information weights.
Bing Han, Dong Hong, Mitch Warachka. Forecast Accuracy Uncertainty and Momentum. Management Science 55 (6) 1035-1046 https://doi.org/10.1287/mnsc.1080.0992