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Hexagon AB (HXGBF) Fair Value & Analysis

Technology · US · Market cap $23.7B

Price$8.37
Fair Value$5.45
Upside-34.9%
Quality95/100
Evidence: High Range $3.88 – $6.81

Analysis

Hexagon AB (HXGBF) currently trades at $8.37, while our model-based Fair Value estimate is $5.45 — implying the stock looks roughly 34.9% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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

Hexagon AB (publ) provides geospatial and industrial enterprise solutions worldwide. It operates in Manufacturing Intelligence, Geosystems, Autonomous Solutions and Octave segments. The company provides autonomy and perception, enterprise software for farms, GNSS positioning, and machine control; airborne and mobile mapping, geospatial content, laser scanning, ERIDAA imagin, lucaid, and M.app enterprise; and asset lifecycle information management, design and visualization, engineering and schematics, enterprise project performance, operations and maintenance, OT/ICS cyber security, and smart digital reality, as well as procurement, fabrication, and construction services. It offers automated measurement systems, CAD/CAM and production software, CAE software, coordinate measuring machines, metrology software, portable measuring systems, quality assurance software, and service and support services. In addition, the company provides evaluation, planning and design; drill and blast; load…

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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.