Two Essays on Sell Side Equity Analysts

Download or read book Two Essays on Sell Side Equity Analysts written by Haosi Chen and published by . This book was released on 2018 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation examines the role of sell side equity analysts in the capital market. The first chapter examines whether sell side analysts, who as an important information intermediary, process information that has been shown to predict future stock returns by academic studies. Our sample includes seven firm level characteristics (e.g., anomalies) that have robust return predictability. We test whether analysts' consensus recommendation and expected returns are consistent with the trading strategies these anomaly variables prescribe. We do not find evidence that sell side analysts are persistently incorporating such information in the correct way. Instead, analysts from certain brokerage firms persistently issue target prices in the opposite direction as what anomaly variables suggests. Our findings suggest that analysts are likely subject to biased expectations and could improve their research quality by incorporating anomaly characteristics. The second chapter investigates whether institutional investors value sell side analysts' qualities differently. We fill the gap in the literature with a novel hand collected dataset, which shows the best sell side analysts voted by hedge funds and institutional investors, respectively. Examining the research output of investors' revealed preferences allows us to detect the qualities valued by these investors. We find that hedge funds preferred analysts update research more frequently and issue less optimistic stock recommendations. The recommendations revised by these analysts also receive stronger market response in the subsequent six months than those made by other "All-Star" sell side analysts. These findings suggest that there are cross sectional differences among sell side analysts that are associated with clients' needs.