Search Based Peer Firms: Aggregating Investor Perceptions through Internet Co-searches
Charles Lee,
Paul Ma and
Charles C. Y. Wang
Additional contact information
Charles C. Y. Wang: ?
Research Papers from Stanford University, Graduate School of Business
Abstract:
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.
Date: 2014-05
New Economics Papers: this item is included in nep-cmp, nep-mfd and nep-sbm
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.gsb.stanford.edu/faculty-research/worki ... -perceptions-through
Related works:
Journal Article: Search-based peer firms: Aggregating investor perceptions through internet co-searches (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:3062
Access Statistics for this paper
More papers in Research Papers from Stanford University, Graduate School of Business Contact information at EDIRC.
Bibliographic data for series maintained by ().