EBMT vs EGBN

Eagle Bancorp Montana, Inc. vs Eagle Bancorp, Inc. — Valuation Comparison 2026

EBMT

Banks - Regional
Eagle Bancorp Montana, Inc.
Quality
8.2
out of 10
Value Trap
10
SAFE
Price
$22.32
Last close
Models
11/13
Active
VS

EGBN

Banks - Regional
Eagle Bancorp, Inc.
Quality
6.8
out of 10
Value Trap
20
SAFE
Price
$27.13
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType EBMT Fair ValueEBMT Upside EGBN Fair ValueEGBN Upside
Bayesian DCF Intrinsic $14.84 -33.5% $22.35 -17.6%
Earnings Power Value Intrinsic $16.68 -25.3% $36.15 +38.3%
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 EBMT vs EGBN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EBMT vs EGBN — Which Stock Is More Undervalued?

EBMT scores higher with a 8.2/10 quality rating vs EGBN's 6.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Eagle Bancorp Montana, Inc. (EBMT) and Eagle Bancorp, Inc. (EGBN) 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.

EBMT currently trades at $22.32 with a QOC of 8.2/10, while EGBN trades at $27.13 with a QOC of 6.8/10.

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).