MYGN vs NTRA

Myriad Genetics, Inc. vs Natera, Inc. — Valuation Comparison 2026

MYGN

Diagnostics & Research
Myriad Genetics, Inc.
Quality
6.6
out of 10
Value Trap
24
SAFE
Price
$4.22
Last close
Models
12/13
Active
VS

NTRA

Diagnostics & Research
Natera, Inc.
Quality
5.1
out of 10
Value Trap
17
SAFE
Price
$213.94
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType MYGN Fair ValueMYGN Upside NTRA Fair ValueNTRA Upside
Bayesian DCF Intrinsic $0.06 -98.5% $17.94 -91.6%
Earnings Power Value Intrinsic $16.62 +293.9% $110.80 -45.6%
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 MYGN vs NTRA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MYGN vs NTRA — Which Stock Is More Undervalued?

MYGN scores higher with a 6.6/10 quality rating vs NTRA's 5.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Myriad Genetics, Inc. (MYGN) and Natera, Inc. (NTRA) 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.

MYGN currently trades at $4.22 with a QOC of 6.6/10, while NTRA trades at $213.94 with a QOC of 5.1/10.

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).