SGS SA (SGSOF) Fair Value & Analysis
Industrials · US · Market cap $23.7B
Fair value as of: Jun 24, 2026
Analysis
SGS SA (SGSOF) currently trades at $111.00, while our model-based Fair Value estimate is $84.16 — implying the stock looks roughly 24.2% overvalued today. We read business quality at 93/100 (high quality), in the Industrials 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
SGS SA operates as a testing, inspection, and certification company in the Asia Pacific, Europe, North America, Eastern Europe, the Middle East and Africa, and America. It operates in two segments, Testing & Inspection and Certification. The company offers testing services, such as crop production testing, agricultural commodities testing, field studies, laboratory studies, seed quality control, and seed research and development; and inspection services, including draft survey and marine services, e-certificates, loading and discharge supervision, pre-shipment inspection, quality and quantity inspection, and tally. It also provides consulting, digital trust assurance, medical devices regulatory compliance, product certification, supply chain assurance, sustainability assurance, and verification and assurance, as well as assessment, auditing, and certification services; and professional training services. The company serves agriculture and forestry, building and infrastructure, consu…
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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.