Fu Chun Shin Machinery Manufacture Co (6603) Fair Value & Analysis
Industrials · TW · Market cap 3.7B TWD
Fair value as of: Jun 24, 2026
Analysis
Fu Chun Shin Machinery Manufacture Co (6603) currently trades at 24.30 TWD, while our model-based Fair Value estimate is 11.82 TWD — implying the stock looks roughly 51.4% overvalued today. We read business quality at 92/100 (high quality), in the Industrials 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
Fu Chun Shin Machinery Manufacture Co., Ltd. engages in the manufacturing, processing, trading, and repair of plastic injection machine and molds, electric wires and cables, and plastic products in Taiwan, Mainland China, and internationally. It offers single injection products, including all-electric, hydraulic, outward toggle, high-speed thin-wall, high-speed, two-platen, servo power-saving, and PET preform injection molding machines, as well as SA-h IMM for PET blood collection tubes. The company also provides multi-injection products, including rotary table and shaft two-component, sandwich/interval, and horizontal rotary table two-component injection molding machines. In addition, it offers special materials, including thermosetting, BMC, PVC pipe, and PET perform injection molding machines. Further, the company provides mold labeling turnkey, beverage packaging, gas assisted injection molding system, microcellular foaming injection molding machine, high precision injection mol…
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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.