ESTA vs EW

Establishment Labs Holdings Inc vs Edwards Lifesciences Corporatio — Valuation Comparison 2026

ESTA

Orthopedic, Prosthetic & Surgical Appliances & Supplies
Establishment Labs Holdings Inc
Quality
6.9
out of 10
Value Trap
6
SAFE
Price
$70.69
Last close
Models
10/13
Active
VS

EW

Orthopedic, Prosthetic & Surgical Appliances & Supplies
Edwards Lifesciences Corporatio
Quality
9.2
out of 10
Value Trap
6
SAFE
Price
$86.47
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType ESTA Fair ValueESTA Upside EW Fair ValueEW Upside
Bayesian DCF Intrinsic $18.70 -73.5% $25.18 -70.9%
Earnings Power Value Intrinsic $2.16 -96.9% $25.40 -70.6%
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 $•••.•• ••.•% $•••.•• ••.•%
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ESTA vs EW — Which Stock Is More Undervalued?

EW scores higher with a 9.2/10 quality rating vs ESTA's 6.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Establishment Labs Holdings Inc (ESTA) and Edwards Lifesciences Corporatio (EW) 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.

ESTA currently trades at $70.69 with a QOC of 6.9/10, while EW trades at $86.47 with a QOC of 9.2/10.

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).