SMBK vs STEL

SmartFinancial, Inc. vs Stellar Bancorp, Inc. — Valuation Comparison 2026

SMBK

Banks - Regional
SmartFinancial, Inc.
Quality
8.2
out of 10
Value Trap
14
SAFE
Price
$41.73
Last close
Models
11/13
Active
VS

STEL

Banks - Regional
Stellar Bancorp, Inc.
Quality
8.1
out of 10
Value Trap
26
LOW
Price
$37.49
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType SMBK Fair ValueSMBK Upside STEL Fair ValueSTEL Upside
Bayesian DCF Intrinsic $38.76 -7.1% $22.55 -39.8%
Earnings Power Value Intrinsic $49.47 +18.5% $33.63 -10.3%
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 SMBK vs STEL — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

SMBK vs STEL — Which Stock Is More Undervalued?

SMBK scores higher with a 8.2/10 quality rating vs STEL's 8.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing SmartFinancial, Inc. (SMBK) and Stellar Bancorp, Inc. (STEL) 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.

SMBK currently trades at $41.73 with a QOC of 8.2/10, while STEL trades at $37.49 with a QOC of 8.1/10.

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).