Jarllytec Co (3548) Fair Value & Analysis
Technology · TW · Market cap 6.2B TWD
Fair value as of: Jun 24, 2026
Analysis
Jarllytec Co (3548) currently trades at 86.80 TWD, while our model-based Fair Value estimate is 71.81 TWD — implying the stock looks roughly 17.3% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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
Jarllytec Co. , Ltd. designs, develops, manufactures, assembles, testing, and trading of stamping parts, hinges, and metal injections/MIM in China, the United States, Thailand, Vietnam, Taiwan, and internationally. The company offers hinge for Foldable Phone, laptops; automatic lowering and automatic lifting equipment. It also offers web camera, camera screen flip structures, headset accessory hub, eyeglass hinges, AR and VR pivots, and e-sports entertainment accessories. In addition, the company provides mobile phone car and bicycle holder, image adjustment, flat fixed, motorized module and automotive display hinges. Further, it offers flat panel monitor stand, fiber optic connector; and other precision parts. Additionally, the company engages in computer design and investment related business, as well as offers powder metallurgy and other metal products, and specific materials for component equipment. Jarllytec Co. , Ltd. was founded in 1992 and is based in New Taipei City, Taiwan.
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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.