Anhui Quanchai Engine Co (600218) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 3.5B CNY
Analysis
Anhui Quanchai Engine Co (600218) currently trades at ¥7.84, while our model-based Fair Value estimate is ¥3.36 — implying the stock looks roughly 57.1% overvalued today. We read business quality at 94/100 (high quality), in the Consumer Cyclical 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
Anhui Quanchai Engine Co., Ltd. engages in the research and development, manufacture, and sale of engines in China, Southeast Asia, Central Asia, Europe, South America, the Middle East, Africa, and internationally. The company offers vehicle diesel engines, petrol engines, agricultural equipment diesel engines, forklift diesel engines, construction machinery diesel engines, generator set diesel engines, and water pump sets diesel engines. It is also involved in the production and sales of gearboxes, main reducers, and engineering plastic parts; research and development, production, and sale of plastic pipes and other plastic products, pipe fittings, and raw and auxiliary materials required for pipe production; wholesale and retail of automobiles, agricultural machinery, construction machinery, and spare parts; design of tooling and fixtures for automobiles, construction machinery, agricultural equipment and related parts; casting, manufactures and sales; fuel cell system technology …
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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.