Vesuvius plc (VSVS) Fair Value & Analysis
Basic Materials · GB · Market cap 1.1B GBX
Analysis
Vesuvius plc (VSVS) currently trades at p4.55, while our model-based Fair Value estimate is p3.25 — implying the stock looks roughly 28.6% overvalued today. We read business quality at 88/100 (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: medium).
About the company
Vesuvius plc provides molten metal flow engineering and technology services to steel and foundry casting industries worldwide. It operates through Steel Flow Control, Steel Advanced Refractories, Steel Sensors & Probes, and Foundry segments. The company offers feeder sleeves and risers, including insulating, exothermic insulating, and highly exothermic sleeves, as well as boards, lids, and powders. It also provides coatings for sand moulds and cores comprising high-production foundry jobbing, foundry coating equipment, and speciality foundry coatings; filters and gating systems for steel, iron, and nonferrous castings; metal treatment products; refractory linings and flow control products, such as furnace linings, ladle linings, and stoppers and nozzles for iron and steel foundries; die coatings for permanent mould casting; and crucibles and retorts under the Salamander and Noltina brands. In addition, the company offers organic and inorganic mould and core binder systems, including…
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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.