Analysts' forecast error: a robust prediction model and its short-term trading profitability

Authors

  • Kris Boudt,

    1. Solvay Business School, Vrije Universiteit Brussel, Brussel, Belgium
    2. Faculty of Economics and Business, V.U.University of Amsterdam, Amsterdam, The Netherlands
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  • Peter de Goeij,

    1. Department of Finance, Tilburg University, Tilburg, The Netherlands
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  • James Thewissen,

    1. Solvay Business School, Vrije Universiteit Brussel, Brussel, Belgium
    2. Faculty of Business and Economics, KU Leuven, Leuven, Belgium
    3. Faculty of Business and Economics @ HUBrussel, KU Leuven, Leuven, Belgium
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  • Geert Van Campenhout

    1. Faculty of Business and Economics, KU Leuven, Leuven, Belgium
    2. Faculty of Business and Economics @ HUBrussel, KU Leuven, Leuven, Belgium
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  • Part of the research was carried out thanks to financial support of the Dutch Science Foundation, the Intercollegiate Center for Management Science, the Junior Mobility Program of the KU Leuven and the National Bank of Belgium. We thank the Editor, Steven Cahan, the Associate Editor, Anne Wyatt, and an anonymous referee, as well as Jean-Yves Gnabo and Stephen Young for their valuable comments.

Abstract

This paper contributes to the empirical evidence on the investment horizon salient to trading based on predicting the error in analysts' earnings forecasts. An econometric framework is proposed that accommodates the stylized fact of extreme values in the forecast error series. We find that between 1998 and 2010, the strategy of taking a long (short) position in stocks with the most pessimistic (optimistic) I/B/E/S forecast has an annual risk-adjusted return of 16.56 per cent before transaction costs. The robust method used to predict this pessimism (optimism) and the one-week investment horizon are the key drivers of the strategy's profitability.

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