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Silicius Real Estate Socimi, S.A (YSIL) Fair Value & Analysis

Real Estate · ES · Market cap €281M

Price€11.00
Fair Value€7.87
Upside-28.5%
Quality95/100
Evidence: High Range €5.90 – €7.87

Fair value as of: Jun 26, 2026

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Analysis

Silicius Real Estate Socimi, S.A (YSIL) currently trades at €11.00, while our model-based Fair Value estimate is €7.87 — implying the stock looks roughly 28.5% 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: high).

About the company

Silicius Real Estate Socimi, S.A. purchases and manages real estate assets in Spain. Its portfolio of assets include retail, offices, hotels, shopping centers, residential, and logistics. The company is based in Madrid, Spain.

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Frequently asked questions

Is Silicius Real Estate Socimi, S.A (YSIL) undervalued?
As of Jun 26, 2026, our model estimates a fair value of €7.87 versus a price of €11.00 — about −28% (overvalued). Model-based estimate, not financial advice.
What is the fair value of YSIL?
Our 21-model fair value for Silicius Real Estate Socimi, S.A is €7.87 (as of Jun 26, 2026), built from audited fundamentals. The current price is €11.00.
What is the quality score of YSIL?
Silicius 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.