CUBE vs DEA

CubeSmart vs Easterly Government Properties, — Valuation Comparison 2026

CUBE

Real Estate Investment Trusts
CubeSmart
Quality
9.7
out of 10
Value Trap
24
SAFE
Price
$40.00
Last close
Models
13/13
Active
VS

DEA

Real Estate Investment Trusts
Easterly Government Properties,
Quality
7.9
out of 10
Value Trap
12
SAFE
Price
$23.98
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType CUBE Fair ValueCUBE Upside DEA Fair ValueDEA Upside
Bayesian DCF Intrinsic $43.74 +9.4% $39.45 +64.5%
Earnings Power Value Intrinsic $10.66 -73.3%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $66.14 +65.4% $20.32 -15.2%
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 CUBE vs DEA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CUBE vs DEA — Which Stock Is More Undervalued?

CUBE scores higher with a 9.7/10 quality rating vs DEA's 7.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing CubeSmart (CUBE) and Easterly Government Properties, (DEA) 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.

CUBE currently trades at $40.00 with a QOC of 9.7/10, while DEA trades at $23.98 with a QOC of 7.9/10.

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).