OPHC vs ORRF

OptimumBank Holdings, Inc. vs Orrstown Financial Services, In — Valuation Comparison 2026

OPHC

Banks - Regional
OptimumBank Holdings, Inc.
Quality
8.8
out of 10
Value Trap
12
SAFE
Price
$5.55
Last close
Models
9/13
Active
VS

ORRF

Banks - Regional
Orrstown Financial Services, In
Quality
9.6
out of 10
Value Trap
18
SAFE
Price
$37.13
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType OPHC Fair ValueOPHC Upside ORRF Fair ValueORRF Upside
Bayesian DCF Intrinsic $0.82 -85.3% $22.92 -38.3%
Earnings Power Value Intrinsic $7.81 +40.8% $47.91 +29.0%
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 OPHC vs ORRF — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

OPHC vs ORRF — Which Stock Is More Undervalued?

ORRF scores higher with a 9.6/10 quality rating vs OPHC's 8.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing OptimumBank Holdings, Inc. (OPHC) and Orrstown Financial Services, In (ORRF) 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.

OPHC currently trades at $5.55 with a QOC of 8.8/10, while ORRF trades at $37.13 with a QOC of 9.6/10.

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).