DingZing Advanced Materials Inc (6585) Fair Value & Analysis
Basic Materials · TW · Market cap 9.7B TWD
Fair value as of: Jun 24, 2026
Analysis
DingZing Advanced Materials Inc (6585) currently trades at 142.00 TWD, while our model-based Fair Value estimate is 95.74 TWD — implying the stock looks roughly 32.6% overvalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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
DingZing Advanced Materials Inc. researches, develops, produces, and sells composite materials, technical films, and other components for various industries in Taiwan. The company's products include Provecta series of advanced technical films that provide an alternative to rubber and traditional plastic; Advanta technical films for waterproof functionality and outstanding breathability; Vulcana, a series of TPU-based yarns for textiles and fabrics; and Orkesta series of composite materials with a layer of hot melt film designed to replace conventional materials, such as microfiber or genuine leather. It also provides perfloa braided, recoil and straight air, and hydration tubes; aldura round, v, and ridgetop belts; and piston, rod, buffer ring, rotary, dust and metal clad wiper. The company's products are used in apparel, footwear, accessories, automotive, healthcare, conveyance, machinery, aerospace, and other industrial use. DingZing Advanced Materials Inc. was founded in 1970 and…
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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.