Macquarie Group (MCQEF) Fair Value & Analysis
Financial Services · US · Market cap $62.6B
Fair value as of: Jun 25, 2026
Analysis
Macquarie Group (MCQEF) currently trades at $162.44, while our model-based Fair Value estimate is $89.71 — implying the stock looks roughly 44.8% 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
Macquarie Group Limited provides diversified financial services in Australia, New Zealand the Americas, Europe, the Middle East, Africa, and Asia. It operates through four segments: Macquarie Asset Management (MAM); Banking and Financial Services (BFS); Commodities and Global Markets (CGM); and Macquarie Capital. The MAM segment provides investment solutions to clients across various capabilities, including real assets, real estate, credit, equities and multi-asset and secondaries. The BFS segment offers personal banking products comprising home loans, car loans, transaction and savings accounts, and credit cards; wealth management products, such as wrap platform and cash management, financial advisory, and private banking services, as well as investment and superannuation products. It also provides deposit, lending, and payment solutions and services to business clients. The CGM segment provides capital and financing, risk management, and physical execution and logistics solutions …
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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.