China Harzone Industry Corp (300527) Fair Value & Analysis
Industrials · CN · Market cap 7.6B CNY
Analysis
China Harzone Industry Corp (300527) currently trades at ¥7.10, while our model-based Fair Value estimate is ¥1.42 — implying the stock looks roughly 80.0% 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: high).
About the company
China Harzone Industry Corp., Ltd engages in the research and development, production, and sales of emergency traffic engineering equipment in China and internationally. The company offers emergency traffic equipment, such as road equipment series for highways, waterways, aviation, and railway emergency traffics. It also provides emergency rescue disposal equipment, including medical vehicles, high-power long-distance water supply and drainage special vehicles, squad and power cars, command vehicles, snowplow, office vehicles, emergency rescue disposal, emergency rescue obstacle-crossing passage, and HZ-sand-throwing emergency vehicles and launch vehicles. In addition, the company offers fire rescue equipment; and public emergency fitting equipment comprising emergency lighting products, non-woven face masks, emergency kits, gas masks, on-board emergency kits, emergency data lines, multi-purpose vehicle window breakers, and portable fire extinguishers. Further, it offers floating br…
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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.