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Fideicomiso Irrevocable No. F/1523 (FIBRAHD15) Fair Value & Analysis

Real Estate · MX · Market cap 1.0B MXN

Price2.38 MXN
Fair Value5.95 MXN
Upside+150.0%
Quality88/100
Evidence: Medium Range 4.05 MXN – 8.31 MXN

Fair value as of: Jun 26, 2026

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Analysis

Fideicomiso Irrevocable No. F/1523 (FIBRAHD15) currently trades at 2.38 MXN, while our model-based Fair Value estimate is 5.95 MXN — implying the stock looks roughly 150.0% undervalued today. We read business quality at 88/100 (high quality), in the Real Estate 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: medium) — always confirm before acting.

About the company

Fideicomiso Irrevocable No. F/1523 is a real estate investment trust. The firm invests in real estate markets. Fideicomiso Irrevocable No. F/1523 is based in Mexico City, México.

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Frequently asked questions

Is Fideicomiso Irrevocable No. F/1523 (FIBRAHD15) undervalued?
As of Jun 26, 2026, our model estimates a fair value of 5.95 MXN versus a price of 2.38 MXN — about +150% (undervalued). Model-based estimate, not financial advice.
What is the fair value of FIBRAHD15?
Our 21-model fair value for Fideicomiso Irrevocable No. F/1523 is 5.95 MXN (as of Jun 26, 2026), built from audited fundamentals. The current price is 2.38 MXN.
What is the quality score of FIBRAHD15?
Fideicomiso Irrevocable No. F/1523 has a Quality Score of 88/100, 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.