Lotus Pharmaceutical Co (1795) Fair Value & Analysis
Healthcare · TW · Market cap 51.6B TWD
Fair value as of: Jun 24, 2026
Analysis
Lotus Pharmaceutical Co (1795) currently trades at 193.50 TWD, while our model-based Fair Value estimate is 273.14 TWD — implying the stock looks roughly 41.2% undervalued today. We read business quality at 95/100 (high quality), in the Healthcare sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Lotus Pharmaceutical Co., Ltd. engages in the research and development, manufacture, and sale of generic pharmaceutical products in Taiwan, South Korea, the United States, and internationally. Its product portfolio focuses on generics in the fields of oncology, central nervous system, cardiovascular diseases, woman health, and anti-obesity. The company also engages in retail of clinical machines; biotech technological consulting services; sale of pharmaceuticals and medicinal chemical products; marketing activities; market planning and business information services; and consultancy services on health management, health technology, and trading information services. In addition, it offers management consultancy services; pharmaceutical regulatory affairs project management, and data collection and agency services; healthcare consultancy services and operates as a contract research organization. Lotus Pharmaceutical Co., Ltd. was incorporated in 1966 and is headquartered in Taipei City…
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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.