Hangzhou Tigermed Consulting Co (HNGZY) Fair Value & Analysis
Healthcare · US · Market cap $3.4B
Analysis
Hangzhou Tigermed Consulting Co (HNGZY) currently trades at $4.00, while our model-based Fair Value estimate is $3.34 — implying the stock looks roughly 16.5% 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
Hangzhou Tigermed Consulting Co., Ltd, together with its subsidiaries, provides contract research organization services in the People's Republic of China and internationally. The company offers clinical trial operation services, such as clinical pharmacology, registration and regulatory affairs, scientific affairs, medical translation, pharmacovigilance, real-world research, third-party auditing and training, etc. for innovative drugs, generic drugs, and medical devices, as well as supporting services directly related to clinical trials, including clinical operation, clinical trials, and clinical trials management. It also provides clinical trial related and laboratory services in the drug development process comprising data management and statistical analysis, clinical trial site management, subject recruitment, medical imaging, and laboratory services. In addition, the company offers preclinical development services, including medicinal chemistry, compound screening, DMPK, safety …
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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.