SonoScape Medical Corp (300633) Fair Value & Analysis
Healthcare · CN · Market cap 8.2B CNY
Fair value as of: Jun 24, 2026
Analysis
SonoScape Medical Corp (300633) currently trades at ¥18.87, while our model-based Fair Value estimate is ¥9.55 — implying the stock looks roughly 49.4% overvalued today. We read business quality at 95/100 (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
SonoScape Medical Corp., together with its subsidiaries, engages in the research, development, production, and sale of medical diagnosis and treatment equipment in China and internationally. It offers ultrasound medical imaging products comprising trolley and portable color dopplers, B/W ultrasounds, and transducers; endoscopic diagnosis and treatment products consisting of image processors, light sources, gastroenterology and pulmonology products, endoscopic ultrasound, duodenoscopes, and peripheral equipment; minimally invasive surgery solutions, such as camera systems and flexible endoscopes; veterinary ultrasound and endoscopy solutions; and intravascular intervention products. The company also provides face-to-face and online training for ultrasound and endoscopy systems; technical and spare parts support; preventive maintenance, calibration, breakdown repair, and other field services; and upgrade services. In addition, it is involved in the software industry. SonoScape Medical…
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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.