SMT Scharf AG (S188) Fair Value & Analysis
Industrials · DE · Market cap €38.6M
Fair value as of: Jun 25, 2026
Analysis
SMT Scharf AG (S188) currently trades at €6.50, while our model-based Fair Value estimate is €12.22 — implying the stock looks roughly 88.0% undervalued today. We read business quality at 80/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.
About the company
SMT Scharf AG engages in the development, manufacture, and service of transportation equipment and logistics systems for underground mining and tunnel construction. The company operates through four segments: Coal Mining, Mineral Mining, Tunnel Logistics, and Other Industries. It offers monorail and duorail systems, chairlift systems, segment cranes, lifting devices, explosive and placement devices, drilling and splitting tools, construction site cranes, battery and diesel locomotives, muckmasters, lift working platform, cable drive, mini climbers, light electric vehicles, and climbing locomotive products. The company's products are primarily used in hard coal, gold, platinum, copper, nickel, and salt mining activities. It has operations in Germany, Russia and rest of CIS states, Poland, China, Africa, the United States, and internationally. The company was founded in 1941 and is headquartered in Hamm, Germany. SMT Scharf AG operates as a subsidiary of Yankuang Energy Group Company …
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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.