ISTR vs KB

Investar Holding Corporation vs KB Financial Group Inc — Valuation Comparison 2026

ISTR

Banks - Regional
Investar Holding Corporation
Quality
7.2
out of 10
Value Trap
12
SAFE
Price
$28.28
Last close
Models
12/13
Active
VS

KB

Banks - Regional
KB Financial Group Inc
Quality
1.8
out of 10
Value Trap
Price
$101.05
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType ISTR Fair ValueISTR Upside KB Fair ValueKB Upside
Bayesian DCF Intrinsic $12.07 -57.3% $33.69 -66.7%
Earnings Power Value Intrinsic $19.83 -29.9% $45.96 -56.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-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 ISTR vs KB — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ISTR vs KB — Which Stock Is More Undervalued?

ISTR scores higher with a 7.2/10 quality rating vs KB's 1.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Investar Holding Corporation (ISTR) and KB Financial Group Inc (KB) 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.

ISTR currently trades at $28.28 with a QOC of 7.2/10, while KB trades at $101.05 with a QOC of 1.8/10.

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).