AHT Syngas Technology N.V (3SQ1) Fair Value & Analysis
Utilities · DE · Market cap €7.6M
Fair value as of: Jun 25, 2026
Analysis
AHT Syngas Technology N.V (3SQ1) currently trades at €2.82, while our model-based Fair Value estimate is €1.62 — implying the stock looks roughly 42.6% overvalued today. We read business quality at 82/100 (high quality), in the Utilities 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: low).
About the company
AHT Syngas Technology N.V. designs and installs biomass power plants worldwide. The company's plants convert waste materials into energy carriers, gas into fuels, and fuels into energy. It provides processing of residual materials; hydrochar production; generation of synthesis gas and process heat; gas conditioning; electricity, heat, and cooling generation; and extraction of valuable materials services. The company also offers project process services, including pre-planning, overall project cost and offer, detailed planning, manufacturing and pre-installation, delivery, on-site assembly, and handover of the plant; and maintenance contract services; and basic and detailed engineering services. Further, it operates and provides energy. The company was formerly known as Squeezy Sports Nutrition N.V. and changed its name to AHT Syngas Technology N.V. in May 2014. AHT Syngas Technology N.V. was incorporated in 2007 and is based in Bonn, Germany.
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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.