Biotech Sell Side Research
A Retrospective Analysis
In association with Thomson Reuters, BioSci recently undertook a retrospective analysis of biotech sell side analyst coverage over the past 15 years.
In association with Thomson Reuters, BioSci recently undertook a retrospective analysis of biotech sell side analyst coverage over the past 15 years. Thomson provided broad access to all initiation of coverage (IOC) reports for 250 public biotechs over the calendar years 1998 through 2011 — about 2,500 reports in all. We chose the 250 public biotechs based on breadth of analyst coverage, and all biotechs were covered by at least two investment firms. Initiation of coverage reports represented the first coverage of a specific biotech company by an investment firm or new lead analyst at that firm. Each IOC report was at least ten PDF pages ian length.
Over the past 15 years, Piper Jaffray has issued the most biotech IOC reports, with 135 reports to their credit. Piper is followed by Morgan Stanley, Rodman, UBS and Wells Fargo as the most frequent issuers of biotech research coverage, each with 100+ IOC reports. For the analysis that follows, we tracked the 26 most frequent issuers of biotech IOC reports, along with the 17 analysts who were the most prolific lead authors of these reports.
At the outset, it should come as no surprise that roughly three-quarters of these reports are “buy” recommendations, and that hasn’t changed much since new analyst independence rules went into effect in Q4 of 1998. 20% of biotech IOC reports are “neutral” on stock price, with the remaining 5% being “sell” recommendations.
We asked the following key question: What percentage of biotech IOC reports met or exceeded their “buy” recommendation target stock price within 12 months of the report’s issuance? To answer this, we looked up the price of each biotech stock over the 365 days following each IOC report and coded whether or not the stock traded through the report’s target price.
Over the past decade and a half, sell side analysts initiating biotech coverage met or exceeded their buy recommendation target stock price 43% of the time. Piper and ThinkEquity led the dozen most frequent biotech research report issuers by meeting their buy target price in 38% of their reports. Among the next 16 most frequent issuers of biotech research coverage (who still had at least 33 biotech IOC reports apiece), Wedbush, Hambrecht and Canaccord met their buy target price in 40% or more of their reports. Among biotech analysts, Alex To (now at Natexis, formerly at Creit Suisse) led the pack of most prolific IOC authors. He met his buy target price in 50% of his reports.
Upon further analysis, 60% of the buy recommendations have a 12 month target price that’s 40% or more above the stock price on the report date — which makes sense because biotech is a high-risk-high-return kind of industry. We then did a similar analysis just looking at reports that predicted and got a 40+% gain. Overall, sell side analysts initiating biotech coverage met or exceed their buy recommendations involving a 40+% gain in target stock price 34% of the time. Among the most frequent report issuers, Rodman ranked first with 22% of its reports predicting and achieving a 40+% gain. Among other report issuers, Wedbush and Canaccord led with success rates of 39% and 30%, respectively. Top analyst honors go to Joseph Pantginis (of Roth, previously at Merriman and Canaccord). He predicted and got a 40+% gain in 36% of his biotech IOC reports.
Armed with “who” have been the best biotech stock pickers over the past 15 years, we are now turning the spotlight on “why” the winners were successful. For example, the data show that analysts were less likely to meet their target price for companies still in development than for biotechs with one or more products on the market. Analysts were also better predicting target price for biotechs in infection or CNS therapeutic areas than for companies in oncology or cardiovascular diseases.
We intend to explore these and other results, including choice of valuation methods and key assumptions (e.g. PE multiple, discount rate) in forthcoming articles.