Wisdom Of Crowds: Effect Of Analysts Herding Around All Stars

Loading...
Thumbnail Image

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Wisdom Of Crowds: Effect Of Analysts Herding Around All Stars

Published Date

2020-04

Publisher

Type

Thesis or Dissertation

Abstract

I examine the effects of herding by financial analysts on the wisdom of crowds. I identify significant herding of analyst earnings forecasts around forecasts of All Star analysts. Despite the fact that All Stars (and by extension those that herd with All Stars) are more accurate forecasters than their peers, I find that consensus forecast accuracy decreases in the degree of All Star herding, consistent with diminished group performance in the presence of herding as predicted by the popular wisdom of crowds literature (Surowiecki 2005). This is in contrast to prior studies that focus on herding around the consensus forecast and how it affects forecasts of individual analysts. Corroborating my main finding, I also find an increase (decrease) in consensus forecast accuracy in the period after an All Star discontinues (initiates) coverage of a firm. I further find that All Star herding is associated with an increased market response to earnings announcements consistent with herding leading to a greater amount of uncertainty that is resolved by a subsequent earnings release. Overall, my findings suggest that the detrimental effect of analyst herding on the wisdom of crowds leads to a deterioration of firms’ information environments.

Description

University of Minnesota Ph.D. dissertation. 2020. Major: Business Administration. Advisor: Pervin Shroff. 1 computer file (PDF); 47 pages.

Related to

Replaces

License

Collections

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Other identifiers

Suggested citation

Fluharty, Andrew. (2020). Wisdom Of Crowds: Effect Of Analysts Herding Around All Stars. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215156.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.