Maywufa Company (1731) Fair Value & Analysis
Healthcare · TW · Market cap 2.9B TWD
Fair value as of: Jun 24, 2026
Analysis
Maywufa Company (1731) currently trades at 21.70 TWD, while our model-based Fair Value estimate is 20.65 TWD — implying the stock looks roughly 4.8% 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
Maywufa Company Ltd. manufactures and sells hair and skin care products under the Maywufa brand in Taiwan. The company engages in the manufacturing, processing, and distribution of hairdressing products, soap, and cosmetics; distribution, wholesale, and retail trading of various beauty products, health products, and sports equipment; retail and wholesale business of health food, such as vitamin pills and oral liquid nutrients; trading, wholesale, and retail of medical drugs and medical equipment; wholesale and retail sales of food, baby products, and general food products; and wholesale trading and agency business. It also provides consulting and analysis; warehousing services; and mother and baby skin care products under the Mustela brand. In addition, the company provides pharmaceuticals and medical devices, such as PG2 Lyophilized injection for treatment of cancer-related fatigue; AmCad-UT Detection device, an ultrasound CAD for thyroid cancer detection; Bio-Three tablets for the…
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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.