Search-based peer firms: Aggregating investor perceptions through internet co-searches

• 成果类型: Article
• 署名作者: Lee, Charles M. C.; Ma, Paul; Wang, Charles C. Y.
• 署名单位: Stanford University; University of Minnesota System; University of Minnesota Twin Cities; Harvard University
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2015.02.003
• 发表日期: 2015
• 页码: 410-431
• 关键词: Peer firm; EDGAR search traffic; revealed preference; Co-search; Industry classification

摘要

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. (C) 2015 Elsevier B.V. All rights reserved.