Allianz SE (ALIZY) Fair Value & Analysis
Financial Services · US · Market cap $174B
Analysis
Allianz SE (ALIZY) currently trades at $45.83, while our model-based Fair Value estimate is $42.01 — implying the stock looks roughly 8.3% 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
Allianz SE, together with its subsidiaries, provides property-casualty insurance, life/health insurance, and asset management products and services worldwide. The company's Property-Casualty segment offers various insurance products, including motor liability, accident, fire and property, general liability, credit, and travel, and assistance services to private and corporate customers. Its Life/Health segment provides a range of life and health insurance products on an individual and a group basis, such as annuities, endowment and term insurance, and unit-linked and investment-oriented products, as well as private and supplemental health, and long-term care insurance products. The company's Asset Management segment offers institutional and retail asset management products and services to third-party investors comprising equity and fixed income funds, cash, and multi-assets; and alternative investment products that include real estate, infrastructure debt/equity, real assets, liquid …
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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.