Voestalpine AG (VOE) Fair Value & Analysis
Basic Materials · AT · Market cap €8.3B
Analysis
Voestalpine AG (VOE) currently trades at €44.56, while our model-based Fair Value estimate is €24.19 — implying the stock looks roughly 45.7% overvalued today. We read business quality at 93/100 (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
Voestalpine AG processes, develops, manufactures, and sells steel and technology products in Austria, the European Union, and internationally. It operates through five divisions: Steel Division, High Performance Metals Division, Metal Engineering Division, Metal Forming Division, and Holding & Group Services. The Steel division produces hot and cold-rolled steel strips, as well as electrogalvanized, hot-dip galvanized, and organically coated steel strips; heavy plates, and foundry products for the energy sector; and turbine casings. The High Performance Metals division offers special high-alloy tool and high-speed steel for the oil and natural gas, aerospace, and energy engineering industries; utilizing nickel-base and titanium alloys; tool manufacturing, component processing, heat treatment, and coating services; warehousing and preprocessing of special steels; and various services, including logistics, distribution, and processing for the oil and natural gas industries. The Metal …
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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.