Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10475849 | Journal of Financial Economics | 2015 | 22 Pages |
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 and for measuring their relative importance. 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. We also show that co-search intensity captures the degree of similarity between firms. Our results highlight the potential of the collective wisdom of investors - extracted from co-search patterns - in addressing long-standing benchmarking problems in finance.
Related Topics
Social Sciences and Humanities
Business, Management and Accounting
Accounting
Authors
Charles M.C. Lee, Paul Ma, Charles C.Y. Wang,