Wuxi Autowell Technology Co (688516) Fair Value & Analysis
Technology · CN · Market cap 17.6B CNY
Analysis
Wuxi Autowell Technology Co (688516) currently trades at ¥57.89, while our model-based Fair Value estimate is ¥23.91 — implying the stock looks roughly 58.7% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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
Wuxi Autowell Technology Co.,Ltd. manufactures and sells automation equipment for photovoltaic equipment, lithium battery equipment, and semiconductor industries in China. The company offers monocrystal growth furnace, OCZ loader, wafer inspection system, wafer automation pack line, PV cell firing and passivation furnace, PV cells screen printing line, linear printer, law pressure chemical vapor disposable, and laser enhanced metallization machines; PV cell laser cutting, MBB PV cell soldering stringer, automatic bussing, and PV string layup and bussing machines; and junction box welding station and automatic solar module laminators. Further, it provides module pack automatic assembly line, container assembly line, module automatic assembly line, and flexible pack automatic assembly line; and appearance inspection and automatic sorting machines for cylindrical cell. In addition, the company offers aluminum wire bonder, hybrid AOI machine, DB/AB AOI machine, and Automatic epoxy die b…
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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.