Gecina (GFC) Fair Value & Analysis
Real Estate · FR · Market cap €5.4B
Analysis
Gecina (GFC) currently trades at €71.65, while our model-based Fair Value estimate is €75.29 — implying the stock looks roughly 5.1% undervalued today. We read business quality at 95/100 (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
Gecina is a leading operator that fully integrates all real estate expertise, owning, managing, and developing a unique prime portfolio valued at 17.6bn euros as at December 31, 2025. Strategically located in the most central areas of Paris and the Paris Region, Gecina's portfolio includes 1.2 million sq.m of office space and nearly 5,300 residential units. By combining long-term value creation with operational excellence, Gecina offers high-quality, sustainable living and working environments tailored to the evolving needs of urban users. As a committed operator, Gecina enhances its assets with high-value services and dynamic property and asset management, fostering vibrant communities. Through its YouFirst brand, Gecina places user experience at the heart of its strategy. In line with its social responsibility commitments, the Foundation Gecina supports initiatives across four core pillars: disability inclusion, environmental protection, cultural heritage, and housing access. Geci…
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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.