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Tianjin Tianyao Pharmaceuticals Co (600488) Fair Value & Analysis

Healthcare · CN · Market cap 5.2B CNY

Price¥4.52
Fair Value¥2.89
Upside-36.1%
Quality80/100
Evidence: Medium Range ¥1.71 – ¥4.46

Analysis

Tianjin Tianyao Pharmaceuticals Co (600488) currently trades at ¥4.52, while our model-based Fair Value estimate is ¥2.89 — implying the stock looks roughly 36.1% overvalued today. We read business quality at 80/100 (high quality), in the Healthcare 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: medium).

About the company

Tianjin Tianyao Pharmaceuticals Co., Ltd. engages in the research and development, production, and sales of corticosteroids, amino acid active pharmaceutical ingredients (APIs), and preparations in China. The company's primary products comprising corticosteroid raw materials, such as dexamethasone, prednisone, methylprednisolone, and betamethasone product series. The company provides amino acid raw materials, as well as preparations, including injections, ointments, creams, hard capsules, pills, freeze-dried powder injections, inhalation preparations, and tablets. It exports its products to the United States, Southeast Asia, Europe, South America, Africa, and internationally. The company was founded in 1939 and is based in Tianjin, China. Tianjin Tianyao Pharmaceuticals Co., Ltd. operates as a subsidiary of Tianjin Pharmaceutical Group Co., Ltd.

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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.