In this report, the Cowen biotech team reviews what we see as the three major components of valuing a smid-cap biotech company: valuation methodologies, modeling probabilities of success, and building market models. Of note – the Cowen biotech team does not segregate coverage by market cap.
Valuation methodologies do not rely on specialist knowledge. The major differential from other sectors is a heavier focus on strategic M&A value.
Our research analysts dissect and detail the main parts of analyzing small and mid-cap biotech companies:
- – valuation methodologies
- – determining probabilities of success
- – building a therapy’s market model
- – decision points where it’s most useful to consult specialists/KOLs/experts including assessing mechanistic rationale, trial statistics, amenable patient populations, reimbursement hurdles, and probability of approval for programs with mixed data
GENERALISTS BENEFIT FROM BIOTECH STOCK ANALYSIS
Small- and mid-cap names have shown strong performance trends and are now a greater proportion of indices that generalists are benchmarked against. Analyzing smid-cap biotechs has long been considered the wheelhouse of specialists, but the analysis can be somewhat demystified using clearly defined parameters.
Why bother figuring out how these stress-inducing, volatile companies might trade? SMID caps have driven the outperformance of the overall biotech sector in the past few years. Further, the proportion of biotech within many standard performance indices has been growing in the last 2-3 years.
BIOTECH STOCK ANALYSIS DIFFERS FROM TRADITIONAL VALUATION METHODS
Biotech has long appeared to be a specialist’s game, especially mid- and small-cap biotech. Traditional valuation methods do not usually apply as they do for large-cap biotech; the overwhelming majority of smid-cap biotechs are not profitable. Most do not even have revenues.
Small- and mid-cap biotech valuations can seem like a black box to generalists. Metrics like EPS and EV often take a back seat to data catalysts (even just timing of data catalysts), sentiment, and sometimes acquisition premium.