Smith & Nephew plc (SNN) Fair Value & Analysis
Healthcare · US · Market cap $12.4B
Analysis
Smith & Nephew plc (SNN) currently trades at $29.61, while our model-based Fair Value estimate is $28.80 — implying the stock looks roughly 2.7% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare 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
Smith & Nephew plc, together with its subsidiaries, develops, manufactures, markets, and sells medical devices and services in the United Kingdom, the United States, and internationally. The company operates in three segments: Orthopaedics, Sports Medicine & ENT, and Advanced Wound Management. It offers knee implant products for knee replacement procedures; hip implants for revision procedures; trauma and extremities products that include internal and external devices used in the stabilization of severe fractures and deformity correction procedures; and other reconstruction products. The company also provides sports medicine joint repair products comprise instruments, technologies, and implants to perform minimally invasive surgery, as well as treating soft tissue injuries and degenerative conditions of the shoulder, knee, hip, and small joints. In addition, it provides arthroscopic enabling technologies comprising fluid management equipment for surgical access, cameras, digital ima…
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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.