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Fibra Danhos (DANHOS13) Fair Value & Analysis

Real Estate · MX · Market cap 43.7B MXN

Price27.10 MXN
Fair Value49.89 MXN
Upside+84.1%
Quality90/100
Evidence: Medium Range 36.63 MXN – 63.16 MXN

Analysis

Fibra Danhos (DANHOS13) currently trades at 27.10 MXN, while our model-based Fair Value estimate is 49.89 MXN — implying the stock looks roughly 84.1% undervalued today. We read business quality at 90/100 (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

Fibra Danhos is a Mexican trust established primarily to develop, lease, operate, and acquire iconic, premium-quality real estate assets in Mexico. We are committed to the transformation of urban areas in the country, primarily in the Mexico City Metropolitan Area. Our purpose is to create, operate, and innovate with knowledge and passion, developing real estate icons that stand out for their identity and premium quality. Through the acquisition, development, renovation, and management of properties, we have achieved a positive impact on society while expanding and diversifying our portfolio. This includes shopping centers, offices, mixed-use projects, industrial parks, and hotels, all of them iconic and of unbeatable quality. Each one is located in strategic locations and operates sustainably, complying with the highest construction and design standards. Fibra Danhos was incorporated in 1976 in Mexico.

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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.