MRK vs PFE

Merck & Company, Inc. vs Pfizer, Inc. — Valuation Comparison 2026

MRK

Drug Manufacturers - General
Merck & Company, Inc.
Quality
9.8
out of 10
Value Trap
Price
$119.89
Last close
Models
13/13
Active
VS

PFE

Drug Manufacturers - General
Pfizer, Inc.
Quality
6.7
out of 10
Value Trap
24
SAFE
Price
$26.14
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType MRK Fair ValueMRK Upside PFE Fair ValuePFE Upside
Bayesian DCF Intrinsic $45.62 -61.9% $29.31 +12.1%
Earnings Power Value Intrinsic $17.85 -85.1% $32.38 +23.9%
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 MRK vs PFE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MRK vs PFE — Which Stock Is More Undervalued?

MRK scores higher with a 9.8/10 quality rating vs PFE's 6.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Merck & Company, Inc. (MRK) 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.

MRK currently trades at $119.89 with a QOC of 9.8/10, while PFE trades at $26.14 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).