RC vs REGCO

Ready Capital Corporation vs Regency Centers Corporation - 5 — Valuation Comparison 2026

RC

Real Estate Investment Trusts
Ready Capital Corporation
Quality
5.9
out of 10
Value Trap
28
LOW
Price
$1.78
Last close
Models
4/13
Active
VS

REGCO

Real Estate Investment Trusts
Regency Centers Corporation - 5
Quality
7.0
out of 10
Value Trap
12
SAFE
Price
$22.10
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType RC Fair ValueRC Upside REGCO Fair ValueREGCO Upside
Bayesian DCF Intrinsic $81.39 +268.3%
Earnings Power Value Intrinsic $38.11 +72.4%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $3.58 +101.0% $55.56 +151.4%
ML-RIV Intrinsic $1.77 -4.3% $111.15 +402.9%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

RC vs REGCO — Which Stock Is More Undervalued?

REGCO scores higher with a 7.0/10 quality rating vs RC's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Ready Capital Corporation (RC) and Regency Centers Corporation - 5 (REGCO) 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.

RC currently trades at $1.78 with a QOC of 5.9/10, while REGCO trades at $22.10 with a QOC of 7.0/10.

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).