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SmartStop Self Storage REIT, Inc (SMA) Fair Value & Analysis

Real Estate · US · Market cap $1.8B

Price$32.53
Fair Value$20.68
Upside-36.4%
Quality89/100
Evidence: Medium Range $11.69 – $31.99

Analysis

SmartStop Self Storage REIT, Inc (SMA) currently trades at $32.53, while our model-based Fair Value estimate is $20.68 — implying the stock looks roughly 36.4% overvalued today. We read business quality at 89/100 (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: medium).

About the company

SmartStop Self Storage REIT, Inc. is a self-managed REIT with a fully integrated operations team of more than 1,000 self-storage professionals focused on growing the SmartStop Self Storage brand. SmartStop, through its indirect subsidiary, SmartStop REIT Advisors, LLC, also sponsors other self-storage programs and, through its Managed Platform, offers third-party management services in the U.S. and Canada. As of February 20, 2026, SmartStop has an owned or managed portfolio of over 460 operating properties in 35 states, the District of Columbia, and Canada, comprising over 270,000 units and more than 35 million rentable square feet. SmartStop and its affiliates own or manage 49 operating self-storage properties across four provinces in Canada, which total approximately 42,200 units and 4.3 million rentable square feet. SmartStop Self Storage REIT, Inc. was established on January 08, 2013 and is based in Ladera Ranch, United States.

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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.