Caisse régionale de Crédit Agricole Mutuel Atlantique Vendée (CRAV) Fair Value & Analysis
Financial Services · FR · Market cap €1.2B
Analysis
Caisse régionale de Crédit Agricole Mutuel Atlantique Vendée (CRAV) currently trades at €166.00, while our model-based Fair Value estimate is €151.02 — implying the stock looks roughly 9.0% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services 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
Caisse régionale de Crédit Agricole Mutuel Atlantique Vendée provides banking products and services in France. It offers accounts and card services; real estate, personal, credit consolidation, student, work, housing transition, and vehicle loans; saving products; revolving credit; and life, home, car and two wheeler, health and welfare, leisure and daily, and borrower insurance products. The company also provides real estate investment, cash management, collection and payment, funding, trade and export financing, international solutions, financial engineering, asset management, leasing, as well as retirement saving solutions. It serves individuals, private banks, businesses, professionals, farmers, public community and social housing, and associations. The company was incorporated in 2001 and is headquartered in Nantes, France. Caisse régionale de Crédit Agricole Mutuel Atlantique Vendée is a subsidiary of Crédit Agricole S.A.
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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.