Canadian Net Real Estate Investment Trust (CNNRF) Fair Value & Analysis
Real Estate · US · Market cap $97.4M
Fair value as of: Jun 26, 2026
Analysis
Canadian Net Real Estate Investment Trust (CNNRF) currently trades at $4.63, while our model-based Fair Value estimate is $4.59 — implying the stock looks roughly 0.9% 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
Canadian Net Real Estate Investment Trust is an active Trust operating in the Canadian commercial real estate market. The Trust currently trades on the TSX Venture using the ticker symbol NET.UN. The Trust owns and rents commercial real estate properties directly, through its wholly owned subsidiaries and joint ventures. Prior to June 17, 2021, the Trust operated under the name of Fronsac Real Estate Investment Trust. As at September 30, 2025, the Trust held 97 investment properties, 80 residing in the province of Quebec, 8 in the province of Ontario, 8 in the province of Nova Scotia and 1 in the province of New Brunswick. The properties are occupied by 4 distinct groups of tenants composed of: (1) necessity-based retailers, (2) national service station and convenience store chains, (3) quick-service restaurant chains, and (4) others. The quality of the properties in the portfolio allows Canadian Net to maintain a best-in-class occupancy level. As at September 30, 2025, the Trust's …
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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.