Arcadis NV (ARCAD) Fair Value & Analysis
Industrials · NL · Market cap €3.0B
Analysis
Arcadis NV (ARCAD) currently trades at €33.34, while our model-based Fair Value estimate is €51.36 — implying the stock looks roughly 54.0% undervalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Arcadis NV engages in the design, engineering, architecture, and consultancy solutions for natural and built assets in The Americas, Europe, the Middle East, and the Asia Pacific. The company operates through Places, Mobility, Resilience, and Intelligence segments. It provides architecture and urbanism services; and asset management services, such as asset management strategy and planning, asset management decision making and operational optimization, life cycle planning and asset management systems, asset information/condition assessment, risk and review, organization and people, and asset management/O&M. The company also provides business advisory services, including asset strategy and performance, business transformation and resiliency, investment and finance, operations and maintenance, and technology and information; contract solutions; cost and commercial management services; and design and engineering solutions for highways, railways, bridges, tunnels, power utilities, water …
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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.