Vaudoise Assurances Holding (VAHN) Fair Value & Analysis
Financial Services · CH · Market cap CHF 2.4B
Analysis
Vaudoise Assurances Holding (VAHN) currently trades at CHF 780.00, while our model-based Fair Value estimate is CHF 661.21 — implying the stock looks roughly 15.2% 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
Vaudoise Assurances Holding SA provides insurance products and services primarily in Switzerland. The company offers mobility insurance products, including car, motorcycle and scooter, classic car, motorhome, boat, and e-bike insurance, as well as legal protection for traffic; household and private liability, private building, construction, golf, valuable item, and pet insurance, as well as private legal protection insurance products; and computer assistance and troubleshooting, breakdown and home assistance, repatriation and medical care, and travel and cancellation insurance products. It also provides loss of earning due to illness, occupational pension plan, and accident insurance products; property protection solutions, such as business inventory, technical equipment, construction, commercial vehicle, and building insurance products; and corporate civil liability, corporate legal protection, and transport insurance products, as well as business assistance and services; and pensi…
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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.