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Net Lease Office Properties (NLOP) Fair Value & Analysis

Real Estate · US · Market cap $172M

Price$11.11
Fair Value$27.78
Upside+150.0%
Quality94/100
Evidence: High Range $21.60 – $33.95

Fair value as of: Jun 26, 2026

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Analysis

Net Lease Office Properties (NLOP) currently trades at $11.11, while our model-based Fair Value estimate is $27.78 — implying the stock looks roughly 150.0% undervalued today. We read business quality at 94/100 (high quality), in the Real Estate sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.

About the company

Net Lease Office Properties is a publicly traded real estate investment trust that owns a portfolio of high-quality, single-tenant properties located in the U.S. and net leased to corporate tenants operating across a variety of industries. Net Lease Office Properties is based in New York, United States.

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Frequently asked questions

Is Net Lease Office Properties (NLOP) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $27.78 versus a price of $11.11 — about +150% (undervalued). Model-based estimate, not financial advice.
What is the fair value of NLOP?
Our 21-model fair value for Net Lease Office Properties is $27.78 (as of Jun 26, 2026), built from audited fundamentals. The current price is $11.11.
What is the quality score of NLOP?
Net Lease Office Properties has a Quality Score of 94/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

How we calculate Fair Value

Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.

Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.