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How Much Do Analysts Influence Each Other's Forecasts?

Author

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  • Jonathan B. Cohn

    (McCombs School of Business, The University of Texas at Austin, 2110 Speedway Stop - B6600, Austin, TX 78712, USA)

  • Jennifer L. Juergens

    (Drexel University: LeBow College of Business, Gerri C. LeBow Hall, 3220 Market Street, Room 1128, Philadelphia, PA 19104, USA)

Abstract

This paper develops and applies a new approach for disentangling the influence of analysts on each other's earnings forecasts from the effects of correlated information shocks. We estimate that, on average, each cent a new forecast by an analyst is above (below) another analyst's most recent forecast causes the other analyst to revise her forecast upwards (downwards) by between 0.21 and 0.36 cents. More reputable analysts are more influential, while those that tend to be optimistic are less influential and are influenced more by the forecasts of other analysts. We do not find support for career concerns-driven herding or anti-herding. Finally, we find that more influential analysts are more likely to subsequently be ranked as All-Stars and to move from a less to a more prestigious brokerage house, and less likely to leave the analyst profession, suggesting that influence is a desirable characteristic.

Suggested Citation

  • Jonathan B. Cohn & Jennifer L. Juergens, 2014. "How Much Do Analysts Influence Each Other's Forecasts?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 4(03), pages 1-35.
    • Handle: RePEc:wsi:qjfxxx:v:04:y:2014:i:03:n:s2010139214500177
    DOI: 10.1142/S2010139214500177
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    References listed on IDEAS

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    1. Zitzewitz, Eric, 2001. "Measuring Herding and Exaggeration by Equity Analysts and Other Opinion Sellers," Research Papers 1802, Stanford University, Graduate School of Business.
    2. Gallo, Giampiero M. & Granger, Clive W.J. & Jeon, Yongil, 1999. "The Impact of the Use of Forecasts in Information Sets," University of California at San Diego, Economics Working Paper Series qt1w33d4b2, Department of Economics, UC San Diego.
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    Cited by:

    1. Cowan, Arnold R. & Salotti, Valentina, 2020. "Anti-selective disclosure regulation and analyst forecast accuracy and usefulness," Journal of Corporate Finance, Elsevier, vol. 64(C).
    2. Dasgupta, Sudipto & Cen, Ling & Chang, Yuk Ying, 2022. "Do Analysts Learn from Each Other? Evidence from Analysts’ Location Diversity," CEPR Discussion Papers 15057, C.E.P.R. Discussion Papers.

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