NLOP vs NNN

Net Lease Office Properties vs NNN REIT, Inc. — Valuation Comparison 2026

NLOP

Real Estate Investment Trusts
Net Lease Office Properties
Quality
6.3
out of 10
Value Trap
31
LOW
Price
$12.01
Last close
Models
9/13
Active
VS

NNN

Real Estate Investment Trusts
NNN REIT, Inc.
Quality
7.7
out of 10
Value Trap
24
SAFE
Price
$44.51
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType NLOP Fair ValueNLOP Upside NNN Fair ValueNNN Upside
Bayesian DCF Intrinsic $50.89 +323.7% $21.66 -51.3%
Earnings Power Value Intrinsic $4.48 -89.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $3.35 -72.1% $5.55 -87.5%
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 NLOP vs NNN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

NLOP vs NNN — Which Stock Is More Undervalued?

NNN scores higher with a 7.7/10 quality rating vs NLOP's 6.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Net Lease Office Properties (NLOP) and NNN REIT, Inc. (NNN) 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.

NLOP currently trades at $12.01 with a QOC of 6.3/10, while NNN trades at $44.51 with a QOC of 7.7/10.

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).