Tamtron Group (TAMTRON) Fair Value & Analysis
Industrials · FI · Market cap €40.8M
Fair value as of: Jun 25, 2026
Analysis
Tamtron Group (TAMTRON) currently trades at €5.35, while our model-based Fair Value estimate is €2.00 — implying the stock looks roughly 62.6% 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
Tamtron Group Oyj provides advanced weighing solutions in Finland. The company provides on-board, railway, truck, on-board crane, weights, laboratory and check, and crane scales. It also offers industrial scales and dosing devices; weighing components; checkweighers; and weighing terminals. In addition, the company provides installation, verification, calibration, repair and maintenance, engineering and consulting, spare parts, rental scales and leasing, and modernization services; system solutions, such as dosing, weighing and mixing solutions, automation, conveyor, glue kitchens and mixers, battery industry, and weighing and dosing. Further, it offers mScales, that connects scales, data, and business operations; One Cloud, a cloud platform designed specifically for managing timber scales in the forest industry; WNexus, a centralised and scalable solution for weighing data management. The company serves various industries, such as battery materials, chemical industry, earth moving …
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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.