NKSH vs NRIM

National Bankshares, Inc. vs Northrim BanCorp Inc — Valuation Comparison 2026

NKSH

Banks - Regional
National Bankshares, Inc.
Quality
8.2
out of 10
Value Trap
8
SAFE
Price
$35.21
Last close
Models
11/13
Active
VS

NRIM

Banks - Regional
Northrim BanCorp Inc
Quality
9.3
out of 10
Value Trap
34
LOW
Price
$24.74
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType NKSH Fair ValueNKSH Upside NRIM Fair ValueNRIM Upside
Bayesian DCF Intrinsic $23.62 -32.9% $29.28 +18.4%
Earnings Power Value Intrinsic $30.89 -12.3% $26.30 +6.3%
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 NKSH vs NRIM — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

NKSH vs NRIM — Which Stock Is More Undervalued?

NRIM scores higher with a 9.3/10 quality rating vs NKSH's 8.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing National Bankshares, Inc. (NKSH) and Northrim BanCorp Inc (NRIM) 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.

NKSH currently trades at $35.21 with a QOC of 8.2/10, while NRIM trades at $24.74 with a QOC of 9.3/10.

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).