Ningbo Tianyi Medical Appliance Co (301097) Fair Value & Analysis
Healthcare · CN · Market cap 2.9B CNY
Fair value as of: Jun 24, 2026
Analysis
Ningbo Tianyi Medical Appliance Co (301097) currently trades at ¥38.11, while our model-based Fair Value estimate is ¥16.96 — implying the stock looks roughly 55.5% 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: low).
About the company
Ningbo Tianyi Medical Appliance Co., Ltd. engages in the research and development, production, and sale of medical polymer consumables and other medical devices to blood purification and ward nursing fields in China and internationally. It offers hemodialysis tubing, artis piping kits, displacement and replacement fluid tubing, puncture device, dialyzer, hemodialysis concentrate and dry powder, and citric acid disinfectant; CRRT piping and series, plasma perfusion devices and separators, blood filters, waste liquid bags, side port connection tube and pipes, and dialysis replacement fluid bag puncture devices; feeders, feeding extension tubes and nutrient bags, and extended straws; and disposable oxygen tubing, cannula, blood transfusion and rectal air sets, endoscopic flushing tube, sterile syringe and needles, and micro adjustable infusion sets. The company was incorporated in 1998 and is headquartered in Ningbo, 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.