Crowdsourcing peer firms
Subtitle: evidence from EDGAR search traffic
By: Charles M.C. Lee, Paul Ma, Charles C.Y. Wang
Contributors: Wang, Charles C.Y.; Ma, Paul; Harvard Business School
Series: Working paper / Harvard Business School -- 13-048; Working paper (Harvard Business School) -- 13-048
Publisher: Harvard Business School
Published: 2013
Place of publication: Boston]
Language: eng
Number of pages: 46
Work titles: Identifying peer firms
Description: Using Internet traffic patterns from the Securities and Exchange Commission Electronic Data-Gathering, Analysis, and Retrieval (EDGAR) website, we show that firms appearing in chronologically adjacent searches by the same individual are fundamentally similar on multiple dimensions. In fact, traffic-based peer firms identified by our algorithm significantly outperform peer firms based on six-digit Global Industry Classification Standard (GICS) groupings in explaining cross-sectional variations in base firms' stock returns, valuation multiples, forecasted and realized growth rates, research and development expenditures, and various other key financial ratios. Our results highlight the usefulness of EDGAR data, as well as the latent intelligence in search traffic patterns.
Notes: "November 2012. (Revised September 2013.)"--Publisher's Web site.

Revision of Identifying peer firms: evidence from EDGAR search traffic.

Includes bibliographical references (pages 27-28).