BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY: Harnessing the Wisdom of Crowds - Zhi Da\, Professor of Finance\,
  University of Notre Dame.
DTSTART:20170209T130000Z
DTEND:20170209T140000Z
UID:TALK66744@talks.cam.ac.uk
CONTACT:CERF/CF Admin
DESCRIPTION:We examine the impact of herding on the accuracy of consensus 
 earnings forecasts from a crowd-based forecast platform (Estimize.com). By
  tracking user viewing activities\, we monitor the amount of information a
  user views before she makes an earnings forecast. We find that the more p
 ublic information a user views\, the less weight she will put on her priva
 te information. While this improves the accuracy of each individual foreca
 st\, it reduces the accuracy of the consensus forecast\, since useful priv
 ate information is prevented from entering the consensus. Predictable erro
 rs made by “influential users” early on persist in the consensus forec
 ast and result in return predictability at earnings announcements. To addr
 ess endogeneity concerns related to information acquisition choices\, we c
 ollaborate with Estimize.com to run experiments where we restrict the info
 rmation set for randomly selected stocks and users. The experiments confir
 m that “independent” forecasts lead to a more accurate consensus and c
 onvince Estimize.com to switch to a “blind” platform from November 201
 5. Overall\, our findings suggest that the wisdom of crowds can be better 
 harnessed by encouraging independent voices from the participants.
LOCATION:Lecture Theatre 1\, Cambridge Judge Business School\, Trumpington
  Street
END:VEVENT
END:VCALENDAR