Analyst teams

• Main Authors: FANG, Bingxu, HOPE, Ole-Kristian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Teamwork; Analysts; Earnings Forecasts; Diversity; Market Reactions to Analyst Revisions; All-Star Analysts; Cash-Flow Forecasts; DCF Models; LinkedIn; Sell-Side; Education; Gender; Accounting; Finance and Financial Management; Portfolio and Security Analysis
• Online Access: https://ink.library.smu.edu.sg/soa_research/1919; https://ink.library.smu.edu.sg/context/soa_research/article/2946/viewcontent/AnalystTeams_av.pdf
• Institution: Singapore Management University

This paper examines the impact of teamwork on sell-side analysts’ performance. Using a hand-collected sample of over 50,000 analyst research reports, we find that analyst teams issue more than 70% of annual earnings forecasts. In contrast, most prior research implicitly assumes that forecasts are issued by individual analysts. We document that analyst teams generate more accurate earnings forecasts than individual analysts and that the stock market reacts more strongly to forecast revisions issued by teams. Analyst teams also cover more firms, issue earnings forecasts more frequently, and issue less stale forecasts. Analysts working in teams are more likely to be voted as All-Star analysts in the future. Among analyst teams, we show that team size and team member ability are significantly associated with forecast accuracy. Moreover, using detailed analyst background information from LinkedIn, we find that forecast accuracy is positively associated with team diversity based on sell-side experience, educational background, and gender. Additional analyses suggest that analyst teams, especially more diverse ones, are more likely to issue cash-flow forecasts and use discounted cash-flow valuation models in their reports. These findings suggest that teamwork and team diversity play a crucial role in understanding sell-side analysts’ performance.