Momentum Group (MMGRF) Fair Value & Analysis
Industrials · US · Market cap $578M
Analysis
Momentum Group (MMGRF) currently trades at $11.69, while our model-based Fair Value estimate is $6.66 — implying the stock looks roughly 43.0% overvalued today. We read business quality at 87/100 (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
Momentum Group AB (publ) supplies industrial components, industrial services, and related services to the industrial sector in Sweden, Norway, Denmark, Finland, and internationally. The company operates through Industry and Infrastructure segments. It offers ball and rolling bearings, transmissions, engines, filters, and seals; hydraulics, linear technology, and pneumatics products and services; customized rubber products and profiles; hydraulic installation and maintenance services; industrial consumables; measuring devices; and assembly, advisory, and training services. The company also provides flow technology solutions and products, such as WHP, jet spray nozzles, jet spray lances, and flow meter wells; pipeline accessories; mini-treatment plants, septic tanks, pumping stations, rain recovery tanks, and oil separators; high-pressure pumps, test pressure equipment, and gas booster systems; CNG/hydrogen refuelling components and gas detection; pinch and knife gate valves, hose pum…
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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.