Kuehne + Nagel International AG (KHNGF) Fair Value & Analysis
Industrials · US · Market cap $27.9B
Analysis
Kuehne + Nagel International AG (KHNGF) currently trades at $220.99, while our model-based Fair Value estimate is $188.70 — implying the stock looks roughly 14.6% overvalued today. We read business quality at 95/100 (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
Kuehne + Nagel International AG, together with its subsidiaries, provides integrated logistics services in Europe, the Middle East, Africa, the Americas, and the Asia-Pacific. The company operates through four segments: Sea Logistics, Air Logistics, Road Logistics, and Contract Logistics. It offers full loads and less than container loads, reefer cold chain solutions for temperature-sensitive goods, order management, and VinLog, a wine, spirits, and drinks logistics solutions, as well as cargo insurance and customs brokerage; and air freight services, such as air charter services, time-critical logistics, sea-air logistics, airside logistics, customs clearance, and smart labels. The company also provides road logistics include full truck load, less than truck load, and groupage services; and fulfillment, warehouse, and distribution services, such as fulfilment operation, distribution and last mile delivery, in-plant, inventory and order management, packaging, returns management, was…
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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.