Shanghai Beite Technology group Co (603009) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 14.8B CNY
Analysis
Shanghai Beite Technology group Co (603009) currently trades at ¥40.74, while our model-based Fair Value estimate is ¥7.59 — implying the stock looks roughly 81.4% overvalued today. We read business quality at 92/100 (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 Beite Technology group Co., Ltd. engages in the chassis parts, lightweight aluminum alloy, and air-conditioning compressor businesses in China. The company provides chassis-related racks, gears, torsion bars, worms, input shafts, output shafts, IPA assemblies, shock absorber piston rods, differential output shafts, new energy high-precision parts CDC-evo external control valve housings, CDC-ivo internal control valve components, wire-controlled brakes IPB-flange, IPB-piston, etc. It offers aluminum parts, brake-by-wire IPB-flange, IPB-piston, etc.; and aluminum alloy lightweight integrated valve island, battery pack connection block, yoke compressors, and vehicle integrated thermal management systems, etc. The company was formerly known as Shanghai Beite Technology Co., Ltd. and changed its name to Shanghai Beite Technology group Co., Ltd. in November 2025. Shanghai Beite Technology group Co., Ltd. was founded in 2002 and is based 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.