Search based peer firms
Subtitle: aggregating investor perceptions through Internet co-searches
By: Charles M.C. Lee, Paul Ma, Charles C.Y. Wang
Contributors: Wang, Charles C.Y, author; Ma, Paul, author; Harvard Business School
Series: Working paper / Harvard Business School -- 13-048; Working paper (Harvard Business School) -- 13-048.
Publisher: Harvard Business School
Published: 2014
Place of publication: Boston]
Language: eng
Number of pages: 54
Work titles: Crowdsourcing peer firms
Description: Applying a "co-search" algorithm to Internet traffic at the SEC's EDGAR website, we develop a novel method for identifying economically related peer firms. Our results show that firms appearing in chronologically adjacent searches by the same individual (Search Based Peers or SBPs) are fundamentally similar on multiple dimensions. In direct tests, SBPs dominate GICS6 industry peers in explaining cross-sectional variations in base firms' out-of-sample (a) stock returns, (b) valuation multiples, (c) growth rates, (d) R&D expenditures, (e) leverage, and (f) profitability ratios. We show that SBPs are not constrained by standard industry classification and are more dynamic, pliable, and concentrated. Our results highlight the potential of the collective wisdom of investors--extracted from co-search patterns--in addressing long-standing benchmarking problems in finance.
Notes: "November 2012. (Revised September 2013, March 2014.)"--Publisher's Web site.

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

Includes bibliographical references (pages 33-34).