SOS Limited (SOS) Fair Value & Analysis
Financial Services · US · Market cap $17.6M
Fair value as of: Jun 26, 2026
Analysis
SOS Limited (SOS) currently trades at $1.05, while our model-based Fair Value estimate is $1.00 — implying the stock looks roughly 4.6% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services 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: low).
About the company
SOS Limited operates as a blockchain-based and big data-driven marketing solution provider in the People's Republic of China. The company offers marketing data, technology, and solutions for insurance companies and emergency rescue services. It also provides SOS cloud emergency rescue service software as a service platform that offers basic cloud products, such as medical rescue, automobile rescue, financial rescue, and rescue mutual aid card services. In addition, the company offers cooperative cloud systems, including information rescue center, intelligent big data, and intelligent software and hardware; information cloud systems, such as news today and e-commerce today; information security services, and marketing-related data; and technology and solutions for emergency rescue services, such as insurance, finance, medical care, health, automobile, safety and mutual aid, and builds a rescue service system. Further, it provides blockchain and cryptocurrency operations, including ho…
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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.