HCAT vs HQY

Health Catalyst, Inc vs HealthEquity, Inc. — Valuation Comparison 2026

HCAT

Health Information Services
Health Catalyst, Inc
Quality
5.9
out of 10
Value Trap
43
WARN
Price
$1.40
Last close
Models
11/13
Active
VS

HQY

Health Information Services
HealthEquity, Inc.
Quality
9.8
out of 10
Value Trap
12
SAFE
Price
$90.52
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType HCAT Fair ValueHCAT Upside HQY Fair ValueHQY Upside
Bayesian DCF Intrinsic $4.65 +274.7% $58.07 -35.8%
Earnings Power Value Intrinsic $43.18 -52.3%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.29 -79.9% $56.87 -37.2%
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 HCAT vs HQY — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

HCAT vs HQY — Which Stock Is More Undervalued?

HQY scores higher with a 9.8/10 quality rating vs HCAT's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Health Catalyst, Inc (HCAT) and HealthEquity, Inc. (HQY) 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.

HCAT currently trades at $1.40 with a QOC of 5.9/10, while HQY trades at $90.52 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).