IDEAS home Printed from https://ideas.repec.org/a/oup/rfinst/v37y2024i5p1494-1537..html
   My bibliography  Save this article

Noise in Expectations: Evidence from Analyst Forecasts

Author

Listed:
  • Tim de Silva
  • David Thesmar

Abstract

Analyst forecasts outperform econometric forecasts in the short run but underperform in the long run. We decompose these differences in forecasting accuracy into analysts’ information advantage, forecast bias, and forecast noise. We find that noise and bias strongly increase with forecast horizon, while analysts’ information advantage decays rapidly. A noise increase with horizon generates a mechanical reversal in the sign of the error-revision (Coibion-Gorodnichenko) regression coefficient at longer horizons, independently of over-/underreaction. A parsimonious model with bounded rationality and a noisy cognitive default matches the term structures of noise and bias jointly.

Suggested Citation

  • Tim de Silva & David Thesmar, 2024. "Noise in Expectations: Evidence from Analyst Forecasts," The Review of Financial Studies, Society for Financial Studies, vol. 37(5), pages 1494-1537.
  • Handle: RePEc:oup:rfinst:v:37:y:2024:i:5:p:1494-1537.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/rfs/hhad091
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    G17; G24; G40;
    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
    • G40 - Financial Economics - - Behavioral Finance - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oup:rfinst:v:37:y:2024:i:5:p:1494-1537.. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/sfsssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.