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Experts' earning forecasts: bias, herding and gossamer information

Author

Listed:
  • Olivier Guedj

    (Capital Fund Management)

  • Jean-Philippe Bouchaud

    (Science & Finance, Capital Fund Management
    CEA Saclay;)

Abstract

We study the statistics of earning forecasts of US, EU, UK and JP stocks during the period 1987-2004. We confirm, on this large data set, that financial analysts are on average over-optimistic and show a pronounced herding behavior. These effects are time dependent, and were particularly strong in the early nineties and during the Internet bubble. We furthermore find that their forecast ability is, in relative terms, quite poor and comparable in quality, a year ahead, to the simplest `no change' forecast. As a result of herding, analysts agree with each other five to ten times more than with the actual result. We have shown that significant differences exist between US stocks and EU stocks, that may partly be explained as a company size effect. Interestingly, herding effects appear to be stronger in the US than in the Eurozone. Finally, we study the correlation of errors across stocks and show that significant sectorization occurs, some sectors being easier to predict than others. These results add to the list of arguments suggesting that the tenets of Efficient Market Theory are untenable.

Suggested Citation

  • Olivier Guedj & Jean-Philippe Bouchaud, 2004. "Experts' earning forecasts: bias, herding and gossamer information," Science & Finance (CFM) working paper archive 500062, Science & Finance, Capital Fund Management.
    • Handle: RePEc:sfi:sfiwpa:500062
    as

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    References listed on IDEAS

    as
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    2. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2004. "Fluctuations and response in financial markets: the subtle nature of 'random' price changes," Quantitative Finance, Taylor & Francis Journals, vol. 4(2), pages 176-190.
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    Cited by:

    1. Veglio, A. & Marsili, M., 2007. "Stochastic analysis of an agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 631-636.

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    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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