Guangzhou Baiyunshan Pharmaceutical Holdings (600332) Fair Value & Analysis
Healthcare · CN · Market cap 35.3B CNY
Analysis
Guangzhou Baiyunshan Pharmaceutical Holdings (600332) currently trades at ¥20.81, while our model-based Fair Value estimate is ¥30.70 — implying the stock looks roughly 47.5% undervalued today. We read business quality at 89/100 (high quality), in the Healthcare sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.
About the company
Guangzhou Baiyunshan Pharmaceutical Holdings Company Limited engages in the pharmaceutical and healthcare industry in the People's Republic of China and internationally. The company operates through Modern Chinese Medicine Business, Chemical Pharmaceutical Technology Business, Natural Beverage Business, Pharmaceutical Commercial Business, and Other segments. It is involved in the research, development, manufacturing, and sale of chemical drugs, chemical raw materials, and chemical raw material intermediates; and research, development, production, and sale of health products; and wholesale, retail, and import export of Western medicines, traditional Chinese medicines, and medical devices. The company also offers bio-innovation, consumer health, and medical services; Xiaochaihu granules; Qingkailing and Baoji, Xia Sangju product series; Angong Niuhuang, Zishen Yutai, Xiaoke, Huatuo Zaizao, Zhuangyao Jianshen, and Shujin Jianyao pills; compound Danshen and Naoxinqing tablet series; Ban…
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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.