Guizhou Yibai Pharmaceutical Co (600594) Fair Value & Analysis
Healthcare · CN · Market cap 2.6B CNY
Fair value as of: Jun 24, 2026
Analysis
Guizhou Yibai Pharmaceutical Co (600594) currently trades at ¥3.12, while our model-based Fair Value estimate is ¥3.56 — implying the stock looks roughly 14.1% undervalued today. We read business quality at 92/100 (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
Guizhou Yibai Pharmaceutical Co., Ltd. researches, develops, produces, and sells pharmaceutical products in China. It offers products in the form of capsules, tablets, granules, syrups, small-volume injections, freeze-dried powder injections, lyophilized powder injections, pills, and oral solutions in the areas of tumor system, cerebrovascular, respiratory system, rheumatic bone, digestive system, pediatric, anti-infection, anti-inflammatory, analgesic, cancer, orthopedics, digestion, andrology, and urology. The company also engages in investment in the cultivation and breeding projects of medicinal materials; and agricultural products sale, as well as provides market information consulting services for medicinal materials. In addition, it is involved in the research and development, and information consulting services for health food. The company was founded in 1995 and is based in Guiyang, 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.