GROUPE SFPI SA (SFPI) Fair Value & Analysis
Industrials · FR · Market cap €189M
Fair value as of: Jun 25, 2026
Analysis
GROUPE SFPI SA (SFPI) currently trades at €2.12, while our model-based Fair Value estimate is €3.60 — implying the stock looks roughly 69.8% undervalued today. We read business quality at 95/100 (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: high) — always confirm before acting.
About the company
GROUPE SFPI SA designs, manufactures, and markets equipment for the safety industry in Europe and internationally. The company operates through DOM Security, NEU-JKF, MMD, MAC, and Other divisions. It offers closure equipment, such as windows and joinery, shutters and blinds, entrance and garage doors, industrial closures, carpentry, and awnings for building industry under the France Fermetures, Franciaflex, Faber, SIPA Menuiseries, and Wo&Wo brands. The company also provides access and locking solutions for buildings, homeowners, small businesses, and large companies. In addition, it offers air treatment solutions, such as dust removal systems, air filtration and conditioning equipment, pneumatic treatment equipment for production waste, pneumatic transport equipment, industrial fans, etc. Further, the company provides thermal processing and sterilization solutions. GROUPE SFPI SA was founded in 1985 and is headquartered in Paris, France.
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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.