SMCP S.A (SMCP) Fair Value & Analysis
Consumer Cyclical · FR · Market cap €405M
Fair value as of: Jun 24, 2026
Analysis
SMCP S.A (SMCP) currently trades at €4.94, while our model-based Fair Value estimate is €5.67 — implying the stock looks roughly 14.7% undervalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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
SMCP S.A. operates as an apparel and accessories retail company in France and internationally. The company offers suits and coats, ready-to-wear products, bags, shoes and accessories; fluidity and structure, lace and embroidery, knitwear and leather; and clothing, as well as footwear, jewellery, scarves, belts, and other accessories. It also provides trench coats, babydoll dresses, sailor tops, and new workwear products; and urban casual and evening wear; and outerwear and shirts. The company sells its products through a network of points of sale, outlets, and own websites, third-party e-commerce platforms, as well as department store websites under the Sandro, Maje, Claudie Pierlot, and Fursac brands. SMCP S.A. was founded in 1984 and is headquartered in Paris, France.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is SMCP S.A (SMCP) undervalued?
What is the fair value of SMCP?
What is the quality score of SMCP?
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.