PPHC vs ROMA

Public Policy Holding Company, vs Roma Green Finance Limited — Valuation Comparison 2026

PPHC

Consulting Services
Public Policy Holding Company,
Quality
5.5
out of 10
Value Trap
Price
$11.64
Last close
Models
12/13
Active
VS

ROMA

Consulting Services
Roma Green Finance Limited
Quality
5.4
out of 10
Value Trap
14
SAFE
Price
$6.99
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType PPHC Fair ValuePPHC Upside ROMA Fair ValueROMA Upside
Bayesian DCF Intrinsic $10.49 -9.9% $3.22 -53.9%
Earnings Power Value Intrinsic $3.03 -79.3% $0.42 -93.1%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
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 PPHC vs ROMA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PPHC vs ROMA — Which Stock Is More Undervalued?

PPHC scores higher with a 5.5/10 quality rating vs ROMA's 5.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Public Policy Holding Company, (PPHC) and Roma Green Finance Limited (ROMA) 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.

PPHC currently trades at $11.64 with a QOC of 5.5/10, while ROMA trades at $6.99 with a QOC of 5.4/10.

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).