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CAE Inc (CAE) Fair Value & Analysis

Industrials · US · Market cap $8.2B

Price$24.85
Fair Value$20.49
Upside-17.5%
Quality96/100
Evidence: High Range $12.77 – $25.61

Analysis

CAE Inc (CAE) currently trades at $24.85, while our model-based Fair Value estimate is $20.49 — implying the stock looks roughly 17.5% overvalued today. We read business quality at 96/100 (high quality), in the Industrials 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

CAE Inc., together with its subsidiaries, provides training, simulation, and critical operation solutions in Canada, the United States, the United Kingdom, Europe, Asia, the Oceania, Africa, and rest of the Americas. The company operates through two segments, Civil Aviation; and Defense and Security. The Civil Aviation segment offers training solutions for flight, cabin, maintenance, ground personnel, and air traffic controllers in commercial, business, and helicopter aviation; a range of flight simulation training devices; and ab initio pilot training and crew sourcing services, as well as airline operations digital solutions. The Defense and Security segment operates as a training and simulation provider that delivers scalable and platform-independent solutions to enable and enhance force readiness and security for defense forces, original equipment manufacturers (OEMs), government agencies, and public safety organizations. The company was formerly known as CAE Industries Ltd. and…

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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.