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Firstcaution SA (MLFIR) Fair Value & Analysis

Financial Services · FR · Market cap €121M

Price€32.00
Fair Value€7.89
Upside-75.3%
Quality95/100
Evidence: High Range €5.92 – €9.87

Fair value as of: Jun 26, 2026

Analysis

Firstcaution SA (MLFIR) currently trades at €32.00, while our model-based Fair Value estimate is €7.89 — implying the stock looks roughly 75.3% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services 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: high).

About the company

Firstcaution SA provides rental guarantee services in Switzerland. The company offers rental guarantee for commercial and residential lease agreements. It serves private clients, commercial clients, and claims sectors. The company was founded in 2008 and is based in Nyon, Switzerland. Firstcaution SA operates as a subsidiary of Compagnie du Mont-Cervin SA.

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Frequently asked questions

Is Firstcaution SA (MLFIR) undervalued?
As of Jun 26, 2026, our model estimates a fair value of €7.89 versus a price of €32.00 — about −75% (overvalued). Model-based estimate, not financial advice.
What is the fair value of MLFIR?
Our 21-model fair value for Firstcaution SA is €7.89 (as of Jun 26, 2026), built from audited fundamentals. The current price is €32.00.
What is the quality score of MLFIR?
Firstcaution SA has a Quality Score of 95/100, 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.