Shanghai Yongmaotai Automotive Technology Co (605208) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 5.2B CNY
Analysis
Shanghai Yongmaotai Automotive Technology Co (605208) currently trades at ¥15.83, while our model-based Fair Value estimate is ¥4.50 — implying the stock looks roughly 71.6% 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
Shanghai Yongmaotai Automotive Technology Co., Ltd. engages in the research and development, production, and sale of cast aluminum alloy and aluminum alloy parts in China and internationally. The company offers fuel vehicle engine cylinder blocks and heads, oil pans, brackets, turbocharger housings, and gearbox end covers; and new energy vehicle battery pack crossbeam components, module brackets, reducer, motor end, and inverter housing cover plates, as well as automobile air-conditioning compressor cylinder blocks, cylinder heads, brackets, brake calipers, shock towers, and wheel covers. It also provides lower and compressor cylinders, sumps, and bearing caps; auto parts; and aluminum ingot and liquid direct-supply, and renewable resource recycling products. The company serves automobile and auto parts manufacturers. Shanghai Yongmaotai Automotive Technology Co., Ltd. was incorporated in 2002 and is headquartered in Shanghai, China.
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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.