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Metso Oyj (OUKPY) Fair Value & Analysis

Industrials · US · Market cap $14.5B

Price$8.41
Fair Value$6.09
Upside-27.6%
Quality95/100
Evidence: High Range $4.11 – $7.75

Analysis

Metso Oyj (OUKPY) currently trades at $8.41, while our model-based Fair Value estimate is $6.09 — implying the stock looks roughly 27.6% overvalued today. We read business quality at 95/100 (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

Metso Oyj provides technologies, end-to-end solutions, and services for the aggregates, minerals processing, and metals refining industries in Europe, North and Central America, South America, the Asia Pacific, Greater China, Africa, the Middle East, and India. It operates in two segments, Aggregates and Minerals. The company provides various equipment, parts, and services for contractors, aggregates quarries, manufacturing sand, slag recycling, and construction and demolition waste recycling; mobile equipment; and stationary equipment, such as crushers, screens, crushing and screening plants, conveyors, chutes, feeders, and air classifiers. It also offers loading and hauling, crushing, conveying, screening, grinding, floatation, magnetic separation, filtration, material and slurry handling, thickening and clarifying, hydrometallurgy, in-pit crush and convey, tailing management, digital twins, and automation services. In addition, the company provides spare and wear parts, 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.