Landis+Gyr Group (LGYRF) Fair Value & Analysis
Industrials · US · Market cap $1.8B
Analysis
Landis+Gyr Group (LGYRF) currently trades at $65.00, while our model-based Fair Value estimate is $35.29 — implying the stock looks roughly 45.7% 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: medium).
About the company
Landis+Gyr Group AG, together with its subsidiaries, provides integrated energy management solutions to utility sector in the Americas, Europe, the Middle East, Africa, and the Asia Pacific. The company offers smart and non-smart electricity, prepayment electricity, commercial/industrial and grid, and smart gas meters; advanced metering infrastructure solutions; heat and water meters and solutions; prepayment solutions; load control devices; street light controllers; and distribution automation, system deployment, and managed network solutions. It also provides various advanced metering infrastructure offerings, including software, meter data management, installation, implementation, consulting, maintenance support, and related services; and communication modules for water and gas meters. In addition, the company designs, manufactures, markets, and sells products for the smart metering, grid edge intelligence, and smart infrastructure technology solutions. The company was formerly k…
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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.