San Fang Chemical Industry Co (1307) Fair Value & Analysis
Consumer Cyclical · TW · Market cap 14.6B TWD
Fair value as of: Jun 24, 2026
Analysis
San Fang Chemical Industry Co (1307) currently trades at 35.85 TWD, while our model-based Fair Value estimate is 42.00 TWD — implying the stock looks roughly 17.2% undervalued today. We read business quality at 95/100 (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: high) — always confirm before acting.
About the company
San Fang Chemical Industry Co., Ltd. manufactures and sells artificial leather, synthetic resin, and other materials in Taiwan, China, Hong Kong, Southeast Asia, and internationally. The company provides polyurethane synthetic leathers; full grain and nubuck synthetic leathers; fibers, such as multi and mono filaments, recycled dope dyed yarn, and thermoplastic polyester elastomer (TPEE) elastic fibers; and hot melt, TPU+hot melt, TPU, and multi-layer films for shoes, as well as films, hot melt, water-proof tapes, elastic hot melt, and decoration hot melt films for apparel. It also manufactures and sells chemical products; and engages in material processing activities. The company's products are used in sports shoes, balls, equipment and bags, and bicycle saddle materials; hot melt, water-proof tape, and decoration hot melt apparel; and vehicle interiors applications. San Fang Chemical Industry Co., Ltd. was founded in 1973 and is headquartered in Kaohsiung 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.