Biotech HF Materials

Hi everyone,

Currently looking to understand how do Hedge Funds analyse biotech / pharma stocks? Do they use similar models as in the buy-side (classic DCF), or are they more concise or with focus in other methodologies?

I would appreciate any suggestions of materials available in the internet where real templates are available for inspiration. Thanks!

3 Comments
 

When it comes to analyzing biotech/pharma stocks, hedge funds often employ methodologies that differ significantly from traditional buy-side approaches like classic DCF models. Here's what you need to know based on the most helpful WSO content:

Key Methodologies Used by Hedge Funds in Biotech/Pharma Analysis:

  1. NPV Analysis:

    • Net Present Value (NPV) is a cornerstone for biotech valuation. Hedge funds often focus on the probability of drug launches, using benchmarks like:
      • Phase 1: ~20% success probability.
      • Phase 2: ~40% success probability.
      • Phase 3: ~60% success probability.
    • These probabilities are adjusted based on historical data for similar drugs or therapeutic areas.
  2. Focus on Drug-Specific Factors:

    • Hedge funds analyze the molecular target, mechanism of action, clinical data quality, and commercial factors like pricing, patient population, and sales channels.
  3. Equity Research Models:

    • Equity research reports are often used as a framework, but hedge funds critically evaluate these models to identify flawed assumptions or overly optimistic projections.
  4. Scenario Analysis:

    • Given the high volatility and binary outcomes in biotech, scenario analysis is crucial. Hedge funds model best-case, base-case, and worst-case scenarios for drug approvals and market performance.
  5. Discount Rates:

    • Traditional CAPM-based discount rates are often not applicable due to the unique risks in biotech. Instead, companies are bucketed by development stage and size, with progressively lower discount rates applied to larger, more stable companies.
  6. Diligence and Inputs:

    • Hedge funds emphasize diligence by reviewing clinical data, consulting with experts (e.g., doctors, scientists), and analyzing regulatory documents and scientific papers.

Learning Resources and Templates:

  • Fairness Opinions:

    • Look for fairness opinions from biopharma deals as they can provide insights into valuation methodologies.
  • Equity Research Reports:

    • Reviewing multiple equity research models can help you understand divergent assumptions and develop your own valuation approach.
  • Building Your Own Models:

    • Start with SEC filings, investor presentations, and publicly available data. Use these to construct basic models and refine them with inputs from clinical and regulatory research.
  • Evaluate Pharma:

    • Tools like Evaluate Pharma can be helpful for gathering data, though they may not always be comprehensive.
  • Online Forums and Guides:

    • Check out resources like the WSO thread on "Guide to Evaluate a Biotech Company" for detailed insights into NPV analysis and other methodologies.

Caution:

  • Be wary of shorting biotech stocks, as acquisitions can lead to massive premiums (300-600%+), making this a risky strategy.

For templates and inspiration, you might not find ready-made hedge fund models online, but starting with equity research reports and fairness opinions is a practical approach.

Sources: Biotech finance part 2: valuation methodologies and modeling considerations, Biotech finance part 2: valuation methodologies and modeling considerations, Biotech finance: from IB to VC / HF to funded startup

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 

Im sure they use many in-depth traditional financial models like the ones you have mentioned, but I also think that any edge in this field comes from knowing more than anyone else about the actual science behind it. Thus, you see many healthcare groups hiring Phd's/MD's because who knows better about the science behind it than them? So in addition to traditional financial models, I'd imagine they build their own proprietary models on the likelihoods of certain clinical trials being successful, etc. Disclaimer: I do not work in the field but am also interested in this topic so this is just my 2 cents 

 

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