Séché Environnement SA (SECVY) Fair Value & Analysis
Industrials · US · Market cap $598M
Analysis
Séché Environnement SA (SECVY) currently trades at $19.80, while our model-based Fair Value estimate is $15.93 — implying the stock looks roughly 19.5% overvalued today. We read business quality at 83/100 (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: medium).
About the company
Séché Environnement SA engages in the management, recovery, and treatment of waste products for industrial and corporate customers, and local authorities in France, Southern Africa, Latin America, Europe, and Asia. The company offers industrial waste management for hazardous and non-hazardous wastes; household waste management; medical waste treatment solutions; total waste management; rehabilitation of polluted sites and soil; regeneration, purification, and chemical synthesis; and industrial water treatment solutions. It also provides sanitation services; chemical cleaning to decontaminate, maintain, and clean industrial facilities; environment interventions and safeguarding, and industrial accident assistance; low-carbon energy supply; and biodiversity solutions. In addition, the company is involved in management of polluted soil; treatment of PFAS pollution; pyrotechnic remediation; and deconstruction, asbestos removal, and depollution activities. Séché Environnement SA was inco…
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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.