Forecast Accuracy Uncertainty and Momentum

成果类型:
Article
署名作者:
Han, Bing; Hong, Dong; Warachka, Mitch
署名单位:
University of Texas System; University of Texas Austin; Singapore Management University
刊物名称:
MANAGEMENT SCIENCE
ISSN/ISSBN:
0025-1909
DOI:
10.1287/mnsc.1080.0992
发表日期:
2009
页码:
1035-1046
关键词:
momentum uncertainty learning
摘要:
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.
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