Huadian Heavy Industries Co (601226) Fair Value & Analysis
Industrials · CN · Market cap 8.1B CNY
Analysis
Huadian Heavy Industries Co (601226) currently trades at ¥6.90, while our model-based Fair Value estimate is ¥3.01 — implying the stock looks roughly 56.4% overvalued today. We read business quality at 93/100 (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: high).
About the company
Huadian Heavy Industries Co., Ltd. engages in the provision of engineering solutions in China. The company operates through seven segments: Marine Energy, Hydrogen-Based Energy, Next-Generation Coal Power, High-End Steel Structures, Material Transportation, Green and Smart Ports, and New Energy System Equipment. It offers long-distance curved belt conveyors, tubular belt conveyors, ship unloaders, bucket wheel stacker-reclaimers, environmentally friendly circular stockyard stacker-reclaimers, tippers, spoil heaps, four major pipelines, power plant steel structures, wind turbine towers, photovoltaic supports, and container quay cranes. The company offers its products to conveyors, ship loaders/unloaders, stacker-reclaimers, new high-efficiency through-type quay cranes, spoil helicopters, tippers, digital material yard management robots, and intelligent inspection robots industries. The company was founded in 2008 and is based in Beijing, China. Huadian Heavy Industries Co., Ltd. oper…
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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.