H-Power plc (AFGYF) Fair Value & Analysis
Industrials · US · Market cap $210M
Fair value as of: Jun 26, 2026
Analysis
H-Power plc (AFGYF) currently trades at $0.1700, while our model-based Fair Value estimate is $0.0200 — implying the stock looks roughly 88.2% 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: low).
About the company
H-Power plc engages in the development of ammonia-based low carbon hydrogen production and hydrogen-to-power solutions in the United Kingdom. It operates through Sales of fuel cell generators and Rental segments. The company provides an H-Power Tower, an S series fuel cell generators; and L series fuel cell generators. It is also developing an H-power generator " S series fuel cell, a modular compact; H-power generator S+ series fuel cell diesel generator alternative; ammonia cracker, a technology to convert ammonia into hydrogen; and a methanol fuel tower, a technology solution for conversion of carrier fuel methanol into hydrogen. In addition, the company provides various support solutions, including the supply of hydrogen, ammonia or methanol; consultation on fuel consumption and logistics requirements; arranging the sourcing, supply, and delivery of the fuel of choice; consultation or supply of on-site fuel storage; consultation and design of the full power solution based on the…
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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.