SGC vs UA

Superior Group of Companies, In vs Under Armour, Inc. — Valuation Comparison 2026

SGC

Apparel & Other Finishd Prods of Fabrics & Similar Matl
Superior Group of Companies, In
Quality
7.9
out of 10
Value Trap
12
SAFE
Price
$12.79
Last close
Models
13/13
Active
VS

UA

Apparel & Other Finishd Prods of Fabrics & Similar Matl
Under Armour, Inc.
Quality
4.8
out of 10
Value Trap
24
SAFE
Price
$5.73
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType SGC Fair ValueSGC Upside UA Fair ValueUA Upside
Bayesian DCF Intrinsic $21.88 +71.1% $3.04 -47.0%
Earnings Power Value Intrinsic $0.84 -92.8% $9.02 +48.5%
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 SGC vs UA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

SGC vs UA — Which Stock Is More Undervalued?

SGC scores higher with a 7.9/10 quality rating vs UA's 4.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Superior Group of Companies, In (SGC) 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.

SGC currently trades at $12.79 with a QOC of 7.9/10, while UA trades at $5.73 with a QOC of 4.8/10.

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).