Séminaires de recherche

Harnessing the Wisdom of Crowds*


Intervenant : Zhi Da
University of Notre Dame - Mendoza College of Business

3 novembre 2016 - T004 - De 14h00 à 15h15

We examine the negative information externality associated with herding on a crowd-based earnings 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 public information a user views, the less weight she will put on her private information. While this improves the accuracy of each individual forecast, it reduces the accuracy of the consensus forecast, since useful private information is prevented from entering the consensus. Predictable errors made by “influential users” early on persist in the consensus forecast and result in return predictability at earnings announcements. To address endogeneity concerns related to information acquisition choices, we collaborate with Estimize.com to run experiments where we restrict the information set for randomly selected stocks and users. The experiments confirm that “independent” forecasts lead to a more accurate consensus and convince Estimize.com to switch to a “blind” platform from November 2015. Overall, our findings suggest that the wisdom of crowds can be better harnessed by encouraging independent voices from the participants.


Intervenant : Matthieu Bouvard
Desautels Faculty of Management

14 juin 2018 - De 14h00 à 15h15


Intervenant : Mikhail Simutin
Rotman School of Management

7 juin 2018 - De 14h00 à 15h15


Intervenant : Liyan Yang
Rotman School of Management

31 mai 2018 - De 14h00 à 15h15


Intervenant : Anton Lines
Columbia Business School

24 mai 2018 - De 14h00 à 15h15


Intervenant : Ian Martin

17 mai 2018 - De 14h00 à 15h15