The short term prediction of analysts' forecast error
Kris Boudt (),
Peter De Goeij,
James Thewissen () and
Geert Van Campenhout ()
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Kris Boudt: KULeuven, Lessius University College, V.U.University of Amsterdam
Peter De Goeij: Tilburg University
James Thewissen: KULeuven, Lessius University College, HUBrussel
Geert Van Campenhout: Hogeschool-Universiteit Brussel (HUB), KULeuven
No 2012/16, Working Papers from Hogeschool-Universiteit Brussel, Faculteit Economie en Management
We examine the profitability of implementing a short term trading strategy based on predicting the error in analysts' earnings per share forecasts using publicly available information. In the 1998-2010 I/B/E/S data, the strategy of taking a long (short) position in stocks with the most pessimistic (optimistic) consensus forecast and closing the position on the rst post announcement day has an annual gross abnormal return of 16.56%, after correcting for market risk, size, book-to-market and price momentum effects. A key insight is that the profitability of the trading strategy stems from using robust forecasting methods and from focusing on the stocks with the most extreme predicted forecast errors. The trading strategies using least squares regression and/or focusing merely on the sign of the forecast error are not profitable.
Keywords: Financial analysts; Forecast error; Short term prediction; Trading strategy (search for similar items in EconPapers)
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