EPC vs HLN

Edgewell Personal Care Company vs Haleon plc — Valuation Comparison 2026

EPC

Perfumes, Cosmetics & Other Toilet Preparations
Edgewell Personal Care Company
Quality
7.5
out of 10
Value Trap
37
LOW
Price
$17.52
Last close
Models
11/13
Active
VS

HLN

Perfumes, Cosmetics & Other Toilet Preparations
Haleon plc
Quality
9.0
out of 10
Value Trap
Price
$9.06
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType EPC Fair ValueEPC Upside HLN Fair ValueHLN Upside
Bayesian DCF Intrinsic $13.37 +47.6%
Earnings Power Value Intrinsic $12.48 -28.7% $7.00 -22.8%
EROIC Spread Intrinsic $31.36 +79.0% $5.74 -36.6%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 EPC vs HLN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EPC vs HLN — Which Stock Is More Undervalued?

HLN scores higher with a 9.0/10 quality rating vs EPC's 7.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Edgewell Personal Care Company (EPC) and Haleon plc (HLN) 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.

EPC currently trades at $17.52 with a QOC of 7.5/10, while HLN trades at $9.06 with a QOC of 9.0/10.

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).