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Service Properties Trust (SVC) Fair Value & Analysis

Real Estate · US · Market cap $1.1B

Price$1.76
Fair Value$2.55
Upside+44.9%
Quality95/100
Evidence: High Range $2.43 – $7.87

Analysis

Service Properties Trust (SVC) currently trades at $1.76, while our model-based Fair Value estimate is $2.55 — implying the stock looks roughly 44.9% undervalued today. We read business quality at 95/100 (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

Service Properties Trust is a real estate investment trust with approximately 10 billion dollars invested in two asset categories service-focused retail net lease properties and hotels. As of December 31, 2025, SVC owned 760 service-focused retail net lease properties with over 13.6 million square feet throughout the United States. As of December 31, 2025, SVC also owned 94 hotels with over 21,000 guest rooms throughout the United States and in Puerto Rico and Canada. SVC is managed by The RMR Group, a leading U.S. alternative asset management company with over 37 billion dollars in assets under management as of December 31, 2025, and 40 years of institutional experience in buying, selling, financing and operating commercial real estate. Service Properties Trust was established on February 07, 1995. Service Properties Trust is headquartered in Newton, Massachusetts.

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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.