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Mistral Iberia Real Estate SOCIMI, S.A (YMIB) Fair Value & Analysis

Real Estate · ES · Market cap €22.7M

Price€1.05
Fair Value€0.3600
Upside-65.7%
Quality95/100
Evidence: Medium Range €0.1900 – €0.6800

Fair value as of: Jun 26, 2026

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Analysis

Mistral Iberia Real Estate SOCIMI, S.A (YMIB) currently trades at €1.05, while our model-based Fair Value estimate is €0.3600 — implying the stock looks roughly 65.7% overvalued today. We read business quality at 95/100 (high quality), in the Real Estate 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: medium).

About the company

Mistral Iberia Real Estate SOCIMI, S.A., a real estate investment company, invests in real estate and other assets. The company was incorporated in 2018 and is based in Madrid, Spain.

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Frequently asked questions

Is Mistral Iberia Real Estate SOCIMI, S.A (YMIB) undervalued?
As of Jun 26, 2026, our model estimates a fair value of €0.3600 versus a price of €1.05 — about −66% (overvalued). Model-based estimate, not financial advice.
What is the fair value of YMIB?
Our 21-model fair value for Mistral Iberia Real Estate SOCIMI, S.A is €0.3600 (as of Jun 26, 2026), built from audited fundamentals. The current price is €1.05.
What is the quality score of YMIB?
Mistral Iberia Real Estate SOCIMI, S.A 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.