Sampo Corporation (1604) Fair Value & Analysis
Consumer Cyclical · TW · Market cap 8.7B TWD
Fair value as of: Jun 24, 2026
Analysis
Sampo Corporation (1604) currently trades at 23.25 TWD, while our model-based Fair Value estimate is 27.49 TWD — implying the stock looks roughly 18.2% undervalued today. We read business quality at 92/100 (high quality), in the Consumer Cyclical 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: medium) — always confirm before acting.
About the company
Sampo Corporation engages in the manufacture, processing, contracting, wholesaling, retailing, repair, and consignment of electronics, electrochemicals, telecommunications, electrical materials, information, and audio products in Taiwan and internationally. The company offers a range of digital consumer and industrial products, including smart home appliances, LCD TVs, video conference displays, digital signage displays, POS/touch displays, and network-connected devices. It also provides touch, USB, and other LCD displays; MSR products; and customizable features for OEM/ODM. In addition, the company engages in the warehousing and transportation services; real estate trading and leasing activities; food and beverage business; product installation, marketing and promotion of electrics and electrons equipment; investment; and import and export businesses. Further, it is involved in customs clearance, air, ocean, and freight forwarding services, as well as manufactures and sells compres…
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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.