Acelon Chemicals & Fiber Corporation (1466) Fair Value & Analysis
Consumer Cyclical · TW · Market cap 1.6B TWD
Fair value as of: Jun 24, 2026
Analysis
Acelon Chemicals & Fiber Corporation (1466) currently trades at 14.05 TWD, while our model-based Fair Value estimate is 9.50 TWD — implying the stock looks roughly 32.4% overvalued today. We read business quality at 92/100 (high quality), in the Consumer Cyclical 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: medium).
About the company
Acelon Chemicals & Fiber Corporation engages in the production, sales, and supply of chemical fibers for fabrics in Asia, America, and Europe. The company offers filament yarns, including nylon, nylon/polyester conjugate, melange, polypropylene, and polyester yarns; functional yarns, such as cooling, antistatic, moisture wicking, antibacterial, and thermal yarns; and ECO friendly yarns, including bio based nylon, dope dyed, recycled dope dyed color, and recycled polyester and nylon yarns. It also provides non-woven fabrics and man-made fibers. The company provides its products under AcePaleta, AceIce, AceStatic, AceCool, AceHygeia, AceVitality, AceColor, AceColor ECO, and AceECO brands. Its products are used in various end markets, such as ready-made garments, outdoor functional products, household goods, industrial products, etc. The company was founded in 1988 and is based in Changhua, 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.