MRNA vs MRVI

Moderna, Inc. vs Maravai LifeSciences Holdings, — Valuation Comparison 2026

MRNA

Biotechnology
Moderna, Inc.
Quality
7.1
out of 10
Value Trap
8
SAFE
Price
$47.57
Last close
Models
12/13
Active
VS

MRVI

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

Model-by-Model Comparison

ModelType MRNA Fair ValueMRNA Upside MRVI Fair ValueMRVI Upside
Bayesian DCF Intrinsic $131.00 +175.4% $15.68 +238.0%
Earnings Power Value Intrinsic $82.08 +80.9% $0.05 -98.9%
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 MRNA vs MRVI — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MRNA vs MRVI — Which Stock Is More Undervalued?

MRNA scores higher with a 7.1/10 quality rating vs MRVI's 6.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Moderna, Inc. (MRNA) and Maravai LifeSciences Holdings, (MRVI) 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.

MRNA currently trades at $47.57 with a QOC of 7.1/10, while MRVI trades at $4.64 with a QOC of 6.4/10.

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).