Saxlund Group (SAXG) Fair Value & Analysis
Industrials · SE · Market cap 91.1M SEK
Fair value as of: Jun 24, 2026
Analysis
Saxlund Group (SAXG) currently trades at kr 12.25, while our model-based Fair Value estimate is kr 4.24 — implying the stock looks roughly 65.4% 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: medium).
About the company
Saxlund Group AB (publ), an environmental technology group, develops, manufactures, and services plants and equipment for the production of environmental-friendly and resource-efficient energy. The company provides push floor dischargers, sliding frame silo dischargers, tube-feeder biomass reclaimers, hydraulic rotor silo dischargers, trailer docking stations, transportable biomass centres, chain conveyors, screw conveyors, and solids pump products. It also offers complete power station handling system, reception of material from trucks, silo storage and discharge systems, truck loading system, and biomass large scale storage system. The company serves cement, electricity, heat and power production, wood and forest, water and waste management, process, recycling, mining, and other industries. The company was formerly known as Pilum AB (publ.) and changed its name to Saxlund Group AB (publ) in July 2017. Saxlund Group AB (publ) was founded in 1947 and is headquartered in Nacka, Sweden.
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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.