PBYI vs PFE

Puma Biotechnology Inc vs Pfizer, Inc. — Valuation Comparison 2026

PBYI

Pharmaceutical Preparations
Puma Biotechnology Inc
Quality
8.4
out of 10
Value Trap
15
SAFE
Price
$7.17
Last close
Models
12/13
Active
VS

PFE

Pharmaceutical Preparations
Pfizer, Inc.
Quality
6.7
out of 10
Value Trap
24
SAFE
Price
$26.18
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType PBYI Fair ValuePBYI Upside PFE Fair ValuePFE Upside
Bayesian DCF Intrinsic $6.50 -9.3% $29.37 +12.2%
Earnings Power Value Intrinsic $4.28 -40.3% $32.38 +23.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for PBYI vs PFE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PBYI vs PFE — Which Stock Is More Undervalued?

PBYI scores higher with a 8.4/10 quality rating vs PFE's 6.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Puma Biotechnology Inc (PBYI) and Pfizer, Inc. (PFE) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

PBYI currently trades at $7.17 with a QOC of 8.4/10, while PFE trades at $26.18 with a QOC of 6.7/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).