PLCE vs UA

Children's Place, Inc. (The) vs Under Armour, Inc. — Valuation Comparison 2026

PLCE

Apparel Manufacturing
Children's Place, Inc. (The)
Quality
4.8
out of 10
Value Trap
30
LOW
Price
$4.35
Last close
Models
4/13
Active
VS

UA

Apparel Manufacturing
Under Armour, Inc.
Quality
4.7
out of 10
Value Trap
24
SAFE
Price
$5.84
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType PLCE Fair ValuePLCE Upside UA Fair ValueUA Upside
Bayesian DCF Intrinsic $3.73 +16.0% $2.71 -53.6%
Earnings Power Value Intrinsic $16.89 +418.1% $9.02 +48.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 PLCE vs UA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PLCE vs UA — Which Stock Is More Undervalued?

PLCE scores higher with a 4.8/10 quality rating vs UA's 4.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Children's Place, Inc. (The) (PLCE) and Under Armour, Inc. (UA) 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.

PLCE currently trades at $4.35 with a QOC of 4.8/10, while UA trades at $5.84 with a QOC of 4.7/10.

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).