Fairvalue-Calculator Fairvalue-Calculator

NETSTREIT Corp (NTST) Fair Value & Analysis

Real Estate · US · Market cap $1.9B

Price$20.38
Fair Value$8.81
Upside-56.8%
Quality95/100
Evidence: High Range $7.13 – $8.81

Analysis

NETSTREIT Corp (NTST) currently trades at $20.38, while our model-based Fair Value estimate is $8.81 — implying the stock looks roughly 56.8% overvalued today. We read business quality at 95/100 (high quality), in the Real Estate sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).

About the company

NETSTREIT Corp. is an internally managed real estate investment trust based in Dallas, Texas that specializes in acquiring single-tenant net lease retail properties nationwide. The growing portfolio consists of high-quality properties leased to e-commerce resistant tenants with healthy balance sheets. Led by a management team of seasoned commercial real estate executives, NETSTREIT's strategy is to create the highest quality net lease retail portfolio in the country with the goal of generating consistent cash flows and dividends for its investors. NETSTREIT Corp. was incorporated in 2019 in Maryland and is based in Dallas, Texas.

Open the full interactive analysis →

Similar stocks

Simon Property Group (SPG) -48% Realty Income Corporation (R1IN34) -88% Unibail-Rodamco-Westfield SE (UNBLF) -2% Kimco Realty Corporation (KIM) -40% Scentre Group (STGPF) -12% CapitaLand Integrated Commercial Trust (CICT or the Trust) (CPAMF) -43%

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.