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How Informative are the Unpredictable Components of Earnings Forecasts?

Author

Listed:
  • Bert de Bruijn

    (Erasmus University Rotterdam, the Netherlands)

  • Philip Hans Franses

    (Erasmus University Rotterdam, the Netherlands)

Abstract

An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the unpredictable components, which may be viewed as the personal expertise of the earnings forecasters, we see that small adjustments to the model forecasts lead to more forecast accuracy. Based on past track records, it is possible to predict the future track record of individual forecasters.

Suggested Citation

  • Bert de Bruijn & Philip Hans Franses, 2015. "How Informative are the Unpredictable Components of Earnings Forecasts?," Tinbergen Institute Discussion Papers 15-032/III, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20150032
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    References listed on IDEAS

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    1. Narasimhan Jegadeesh & Woojin Kim, 2010. "Do Analysts Herd? An Analysis of Recommendations and Market Reactions," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 901-937, February.
    2. Kim, Yongtae & Lobo, Gerald J. & Song, Minsup, 2011. "Analyst characteristics, timing of forecast revisions, and analyst forecasting ability," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 2158-2168, August.
    3. Brown, Lawrence D., 1993. "Reply to commentaries on "Earnings forecasting research: its implications for capital markets research"," International Journal of Forecasting, Elsevier, vol. 9(3), pages 343-344, November.
    4. Landsman, Wayne R. & Maydew, Edward L. & Thornock, Jacob R., 2012. "The information content of annual earnings announcements and mandatory adoption of IFRS," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 34-54.
    5. Michael B. Clement & Senyo Y. Tse, 2005. "Financial Analyst Characteristics and Herding Behavior in Forecasting," Journal of Finance, American Finance Association, vol. 60(1), pages 307-341, February.
    6. Sheng, Xuguang & Thevenot, Maya, 2012. "A new measure of earnings forecast uncertainty," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 21-33.
    7. Brown, Lawrence D., 1993. "Earnings forecasting research: its implications for capital markets research," International Journal of Forecasting, Elsevier, vol. 9(3), pages 295-320, November.
    8. Clement, Michael B. & Hales, Jeffrey & Xue, Yanfeng, 2011. "Understanding analysts' use of stock returns and other analysts' revisions when forecasting earnings," Journal of Accounting and Economics, Elsevier, vol. 51(3), pages 279-299, April.
    9. Ramnath, Sundaresh & Rock, Steve & Shane, Philip, 2008. "The financial analyst forecasting literature: A taxonomy with suggestions for further research," International Journal of Forecasting, Elsevier, vol. 24(1), pages 34-75.
    10. Bolliger, Guido, 2004. "The characteristics of individual analysts' forecasts in Europe," Journal of Banking & Finance, Elsevier, vol. 28(9), pages 2283-2309, September.
    11. Stickel, Se, 1990. "Predicting Individual Analyst Earnings Forecasts," Journal of Accounting Research, Wiley Blackwell, vol. 28(2), pages 409-417.
    12. Brown, Philip, 1993. "Comments on 'Earnings forecasting research: its implications for capital markets research' by L. Brown," International Journal of Forecasting, Elsevier, vol. 9(3), pages 331-335, November.
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    More about this item

    Keywords

    Earnings Forecasts; Earnings Announcements; Financial Markets; Financial Analysts;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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