ANF vs BURL

Abercrombie & Fitch Company vs Burlington Stores, Inc. — Valuation Comparison 2026

ANF

Apparel Retail
Abercrombie & Fitch Company
Quality
8.5
out of 10
Value Trap
6
SAFE
Price
$82.18
Last close
Models
13/13
Active
VS

BURL

Apparel Retail
Burlington Stores, Inc.
Quality
8.4
out of 10
Value Trap
6
SAFE
Price
$300.52
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType ANF Fair ValueANF Upside BURL Fair ValueBURL Upside
Bayesian DCF Intrinsic $64.95 -21.0% $20.06 -93.7%
Earnings Power Value Intrinsic $64.70 -21.3% $21.89 -92.7%
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 ANF vs BURL — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ANF vs BURL — Which Stock Is More Undervalued?

ANF scores higher with a 8.5/10 quality rating vs BURL's 8.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Abercrombie & Fitch Company (ANF) and Burlington Stores, Inc. (BURL) 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.

ANF currently trades at $82.18 with a QOC of 8.5/10, while BURL trades at $300.52 with a QOC of 8.4/10.

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).