FUSB vs FXNC

First US Bancshares, Inc. vs First National Corporation — Valuation Comparison 2026

FUSB

Banks - Regional
First US Bancshares, Inc.
Quality
8.3
out of 10
Value Trap
14
SAFE
Price
$15.75
Last close
Models
11/13
Active
VS

FXNC

Banks - Regional
First National Corporation
Quality
9.7
out of 10
Value Trap
12
SAFE
Price
$28.04
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType FUSB Fair ValueFUSB Upside FXNC Fair ValueFXNC Upside
Bayesian DCF Intrinsic $19.33 +22.7% $26.73 -4.7%
Earnings Power Value Intrinsic $15.18 -3.6% $39.94 +42.4%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 FUSB vs FXNC — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FUSB vs FXNC — Which Stock Is More Undervalued?

FXNC scores higher with a 9.7/10 quality rating vs FUSB's 8.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing First US Bancshares, Inc. (FUSB) and First National Corporation (FXNC) 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.

FUSB currently trades at $15.75 with a QOC of 8.3/10, while FXNC trades at $28.04 with a QOC of 9.7/10.

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).