REGCP vs RPT

Regency Centers Corporation - 6 vs Rithm Property Trust Inc. — Valuation Comparison 2026

REGCP

Real Estate Investment Trusts
Regency Centers Corporation - 6
Quality
7.0
out of 10
Value Trap
12
SAFE
Price
$23.45
Last close
Models
12/13
Active
VS

RPT

Real Estate Investment Trusts
Rithm Property Trust Inc.
Quality
4.9
out of 10
Value Trap
38
LOW
Price
$14.64
Last close
Models
7/13
Active

Model-by-Model Comparison

ModelType REGCP Fair ValueREGCP Upside RPT Fair ValueRPT Upside
Bayesian DCF Intrinsic $55.57 +137.0%
Earnings Power Value Intrinsic $39.64 +69.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $111.70 +376.4% $32.62 +122.8%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $4.07 -72.4%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for REGCP vs RPT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

REGCP vs RPT — Which Stock Is More Undervalued?

REGCP scores higher with a 7.0/10 quality rating vs RPT's 4.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Regency Centers Corporation - 6 (REGCP) and Rithm Property Trust Inc. (RPT) 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.

REGCP currently trades at $23.45 with a QOC of 7.0/10, while RPT trades at $14.64 with a QOC of 4.9/10.

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).