MRVI vs NAMS

Maravai LifeSciences Holdings, vs NewAmsterdam Pharma Company N.V — Valuation Comparison 2026

MRVI

Biotechnology
Maravai LifeSciences Holdings,
Quality
6.4
out of 10
Value Trap
Price
$4.64
Last close
Models
12/13
Active
VS

NAMS

Biotechnology
NewAmsterdam Pharma Company N.V
Quality
2.3
out of 10
Value Trap
Price
$35.42
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType MRVI Fair ValueMRVI Upside NAMS Fair ValueNAMS Upside
Bayesian DCF Intrinsic $15.68 +238.0% $7.68 -78.3%
Earnings Power Value Intrinsic $0.05 -98.9% $18.09 -39.1%
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 MRVI vs NAMS — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MRVI vs NAMS — Which Stock Is More Undervalued?

MRVI scores higher with a 6.4/10 quality rating vs NAMS's 2.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Maravai LifeSciences Holdings, (MRVI) and NewAmsterdam Pharma Company N.V (NAMS) 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.

MRVI currently trades at $4.64 with a QOC of 6.4/10, while NAMS trades at $35.42 with a QOC of 2.3/10.

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).