文献类型：期刊文献

英文题名：Exploring the profitability in analyst collective opinions: The role of analyst crowd characteristics

作者：Wu, Xianjiao[1];Ye, Qiang[2];Liu, Xiaochen[3];Liu, Xudong[4]

机构：[1]East China Univ Sci & Technol, Sch Business, 130 Meilong Rd, Shanghai, Peoples R China;[2]Univ Sci & Technol, Int Inst Finance, Sch Management, 96 Jinzhai Rd, Hefei, Anhui, Peoples R China;[3]Beijing Jiaotong Univ, Sch Econ & Management, 3 Shangyuan Village, Beijing, Peoples R China;[4]Harbin Inst Technol, Sch Management, 92 Xidazhi St, Harbin, Heilongjiang, Peoples R China

年份：2026

卷号：98

外文期刊名：JOURNAL OF CORPORATE FINANCE

收录：;WOS:【SSCI(收录号:WOS:001677291200001)】；

基金：We gratefully acknowledge the insightful comments and constructive suggestions from Prof. Xuan Tian, the editor, and the two anonymous reviewers. We also thank the National Natural Science Foundation of China for financial support (Grant Nos. 72401099, 72121001, and 72501021) .

语种：英文

外文关键词：Consensus recommendations profitability; Analyst crowd; Crowd size; Connection density; Opinion diversity; Professional experience diversity

摘要：A substantial literature studies the profitability of analyst crowds' consensus recommendations in predicting stock price changes. Nonetheless, uncertainties remain about whether the profitability is contingent upon specific factors, particularly the characteristics of the analyst crowd. This study specifically examines the impact of crowd network structure (crowd size, connection density) and crowd network content (opinion diversity, professional experience diversity) on consensus recommendation profitability. Using comprehensive data from the Chinese stock market, including stock prices, analyst recommendations, and employment histories, we find that consensus recommendations are profitable when they come from larger analyst crowds and when the diversity within these crowds is higher, both in terms of opinion diversity and professional experience diversity. Conversely, consensus recommendations are less likely to be profitable when the analyst crowds maintain denser connections. Moreover, these effects vary across different information environments, including information tone (upgrades or downgrades), stocklevel information uncertainty (high versus low), and information disruptions caused by the COVID-19 pandemic.