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SAS Florentaise (ALFLO) Fair Value & Analysis

Basic Materials · FR · Market cap €5.6M

Price€0.6000
Fair Value€0.5415
Upside-9.8%
Quality91/100
Evidence: Low Range €0.2486 – €0.8344

Fair value as of: Jun 25, 2026

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Analysis

SAS Florentaise (ALFLO) currently trades at €0.6000, while our model-based Fair Value estimate is €0.5415 — implying the stock looks roughly 9.8% overvalued today. We read business quality at 91/100 (high quality), in the Basic Materials 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

SAS Florentaise designs, manufactures, and markets soil mixes, soil improvers, and mulches for professionals and the public in France and internationally. The company offers its products under Florentaise Pro, Terre & Nature Pro, Terre & Nature, Terre au Naturel, and MON JARDIN EN VILLE brand name, as well as offers wood fiber pots under Fertil name. It serves horticulturists, nurseries, market gardeners, and local authorities and landscape business markets, as well as garden centres, DIY stores, and supermarkets. The company was founded in 1973 and is headquartered in Saint-Mars-du-Désert, France.

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Frequently asked questions

Is SAS Florentaise (ALFLO) undervalued?
As of Jun 25, 2026, our model estimates a fair value of €0.5415 versus a price of €0.6000 — about −10% (overvalued). Model-based estimate, not financial advice.
What is the fair value of ALFLO?
Our 21-model fair value for SAS Florentaise is €0.5415 (as of Jun 25, 2026), built from audited fundamentals. The current price is €0.6000.
What is the quality score of ALFLO?
SAS Florentaise has a Quality Score of 91/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.