HyUnion Holding (002537) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 7.0B CNY
Analysis
HyUnion Holding (002537) currently trades at ¥5.97, while our model-based Fair Value estimate is ¥5.63 — implying the stock looks roughly 5.7% overvalued today. We read business quality at 95/100 (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
HyUnion Holding Co.,Ltd engages in the automobile manufacturing industry in China. It operates through Smart Manufacturing Division and Fintech Division segments. The company offers automotive parts, such as instrument panel crossbeams, crash beams, crash bars, threshold beam, seat frame crossbeam assembly, and roller pressed parts; and supply chain products, including stainless steel, hot-dip galvanizing, electro-galvanizing, cold rolling, color painting, and silicon steel. It also provides refrigerated bicycle special purpose vehicles; mold comprising PRG progressive die, TRF continuous mode, and automatic line mold; and electric air conditioner compressor motor, car water pump motor, air conditioner compressor motor, variable frequency compressor motor, cleaning equipment water pump motor, and new energy vehicle cleaning water pump motor. The company was formerly known as Qingdao Haili Metal One Co., Ltd. and changed its name to HyUnion Holding Co., Ltd. in August 2017. HyUnion H…
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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.