Syensqo SA (SYENS) Fair Value & Analysis
Basic Materials · BE · Market cap €6.8B
Analysis
Syensqo SA (SYENS) currently trades at €65.30, while our model-based Fair Value estimate is €62.82 — implying the stock looks roughly 3.8% overvalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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
Syensqo SA/NV, a chemical company, engages in the research, development, and production of advanced materials for industrial and consumer applications worldwide. The company operates through the Materials, Performance & Care, and Other Solutions segments. It offers amine ether, amines, fatty amines, and specialty amines; antioxidants and stabilizers; composites; flavors and fragrances, including vanillin, ethylvanillin, natural vanillin, and cyclopentanone; lithium derivatives; diphenols and hydrocarbon monomers; and phosphorus specialties. The company also provides biobased polymers, inverse emlusion polymers, monomers, specialty monomers, and synthetic polymers; solvents comprising green solvents, flame retardants, and hydrocarbon; specialty chemicals, such as nitric acid; specialty polymers that include aromatic polyamides, aromatics, sulfones, fluorinated fluids, fluoropolymers, high performance polyester, polyethylene, polyolefin, and polyvinylidene chloride; and amphoteric, an…
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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.