MNPR vs MRK

Monopar Therapeutics Inc. vs Merck & Company, Inc. — Valuation Comparison 2026

MNPR

Pharmaceutical Preparations
Monopar Therapeutics Inc.
Quality
4.3
out of 10
Value Trap
6
SAFE
Price
$65.04
Last close
Models
8/13
Active
VS

MRK

Pharmaceutical Preparations
Merck & Company, Inc.
Quality
9.8
out of 10
Value Trap
Price
$118.72
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType MNPR Fair ValueMNPR Upside MRK Fair ValueMRK Upside
Bayesian DCF Intrinsic $20.61 -68.3% $67.39 -43.2%
Earnings Power Value Intrinsic $17.85 -85.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $6.22 -90.4% $46.33 -61.0%
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 MNPR vs MRK — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MNPR vs MRK — Which Stock Is More Undervalued?

MRK scores higher with a 9.8/10 quality rating vs MNPR's 4.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Monopar Therapeutics Inc. (MNPR) and Merck & Company, Inc. (MRK) 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.

MNPR currently trades at $65.04 with a QOC of 4.3/10, while MRK trades at $118.72 with a QOC of 9.8/10.

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).