National Grid plc (NGG) Fair Value & Analysis
Utilities · US · Market cap $79.1B
Analysis
National Grid plc (NGG) currently trades at $81.57, while our model-based Fair Value estimate is $65.73 — implying the stock looks roughly 19.4% overvalued today. We read business quality at 97/100 (high quality), in the Utilities 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
National Grid plc engages in the transmission and distribution of electricity and gas. It operates through UK Electricity Transmission, UK Electricity Distribution, New England, New York, National Grid Ventures, and Other segments. The UK Electricity Transmission segment provides electricity transmission networks in England and Wales. The UK Electricity Distribution segment offers electricity distribution services in east and west Midlands, Southwest of England, and South Wales. The New England segment provides electricity and gas supply and distribution, and high-voltage electricity transmission services in New England. The New York segment offers electricity and gas distribution, and electricity transmission services in New York. The National Grid Ventures segment provides transmission services through electricity interconnectors and LNG importation at the Isle of Grain. The Other segment engages in the leasing and sale of commercial property, as well as insurance activities in th…
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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.