Jinlei Technology Co (300443) Fair Value & Analysis
Industrials · CN · Market cap 7.4B CNY
Analysis
Jinlei Technology Co (300443) currently trades at ¥22.77, while our model-based Fair Value estimate is ¥14.79 — implying the stock looks roughly 35.0% overvalued today. We read business quality at 93/100 (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
Jinlei Technology Co., Ltd., together with its subsidiaries, engages in the research, development, manufacture, machining, and sale of wind turbine main shafts, and various castings and forgings in China and internationally. The company provides fan spindle products comprising forged and casting shafts, and spindle accessories; and free forging products, including cylinders, discs, and other special-shaped forgings. It offers new energy power equipment; bearings, gears, and transmission parts; and plastic and polymer composite products. In addition, the company engages in the development, production, and sale of wind and solar power generation projects; commodity wholesale; and import and export of mechanical parts. It serves the wind power, hydropower, thermal power, mining, metallurgy, petrochemical, shipbuilding, and mold industries. The company was formerly known as Shandong Laiwu Jinlei Wind Power Technology Co., Ltd. and changed its name to Jinlei Technology Co., Ltd. in Febru…
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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.