Suzhou Hailu Heavy Industry Co (002255) Fair Value & Analysis
Industrials · CN · Market cap 8.2B CNY
Fair value as of: Jun 25, 2026
Analysis
Suzhou Hailu Heavy Industry Co (002255) currently trades at ¥9.40, while our model-based Fair Value estimate is ¥10.54 — implying the stock looks roughly 12.1% undervalued today. We read business quality at 94/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Suzhou Hailu Heavy Industry Co.,Ltd designs, manufactures, and sells industrial waste heat boilers, large and special material pressure vessels, and nuclear safety equipment. It offers boiler products, such as high efficiency pulverized coal boiler, CFB boiler, coal gasification heat recovery boiler, CDQ heat recovery boiler and heat recovery system, oxygen converter heat recovery boiler, and its heat recovery system, blast furnace gas heat recovery boiler, heating furnace heat recovery boiler, sulphuric acid plant waste heat boiler, oil refining catalyst unit heat recovery boiler, sintering waste heat boiler, HRSG, BFB boiler, etc. The company also provides pressure vessels for coal chemical, petrochemical chemistry, and fine chemistry; nuclear products, including nuclear power products, reactor vessel internals barrel shells, primary heat exchanger, and primary circuit tanks; environmental engineering products; and cryogenic products. Suzhou Hailu Heavy Industry Co.,Ltd was founde…
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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.