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Shenzhen Salubris Pharmaceuticals Co (002294) Fair Value & Analysis

Healthcare · CN · Market cap 33.8B CNY

Price¥30.78
Fair Value¥11.87
Upside-61.4%
Quality91/100
Evidence: High Range ¥7.94 – ¥14.84

Analysis

Shenzhen Salubris Pharmaceuticals Co (002294) currently trades at ¥30.78, while our model-based Fair Value estimate is ¥11.87 — implying the stock looks roughly 61.4% overvalued today. We read business quality at 91/100 (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: high).

About the company

Shenzhen Salubris Pharmaceuticals Co., Ltd. engages in the research, development, production, and sale of pharmaceuticals and medical devices in China. The company is involved in the production and supply of pharmaceutical products in the fields of chronic diseases, including cardiovascular and cerebrovascular diseases, diabetes, oncology, osteoporosis, anti-infective diseases, and chronic kidney diseases. It also engages in the research and development, production, and sale of high-end interventional medical devices, such as cardiovascular and cerebrovascular, peripheral vascular, structural heart disease, electrophysiology, and cardiac rhythm management. The company was incorporated in 1998 and is headquartered in Shenzhen, China. Shenzhen Salubris Pharmaceuticals Co., Ltd. operates as a subsidiary of Salubris Pharmaceuticals 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.