Search based peer firms

aggregating investor perceptions through Internet co-searches

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Author

Charles M. C. Lee

Contributions

Wang, Charles C.Y, author - Contributor
Ma, Paul, author - Contributor
Harvard Business School - Contributor

Publication

2014 - Harvard Business School, Boston, Massachusetts

Language

English

Word Count

13,500 words, Guess

Page Count

54 pages

Identifiers

OCLC Control Number878840366
OCLC Control Number881685065
OCLC Control Number884988784
Open LibraryOL43062151M

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.

Subjects

Series Statement

Working paper / Harvard Business School -- 13-048

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