PSTL vs REGCO

Postal Realty Trust, Inc. vs Regency Centers Corporation - 5 — Valuation Comparison 2026

PSTL

Real Estate Investment Trusts
Postal Realty Trust, Inc.
Quality
7.6
out of 10
Value Trap
24
SAFE
Price
$23.04
Last close
Models
12/13
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 PSTL Fair ValuePSTL Upside REGCO Fair ValueREGCO Upside
Bayesian DCF Intrinsic $4.64 -79.8% $81.39 +268.3%
Earnings Power Value Intrinsic $38.11 +72.4%
EROIC Spread Intrinsic $1.42 -93.9% $36.79 +66.5%
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 PSTL vs REGCO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PSTL vs REGCO — Which Stock Is More Undervalued?

PSTL scores higher with a 7.6/10 quality rating vs REGCO's 7.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Postal Realty Trust, Inc. (PSTL) 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.

PSTL currently trades at $23.04 with a QOC of 7.6/10, 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).