Tachia Yung Ho Machine Industry Co (2221) Fair Value & Analysis
Basic Materials · TW · Market cap 1.8B TWD
Fair value as of: Jun 24, 2026
Analysis
Tachia Yung Ho Machine Industry Co (2221) currently trades at 49.70 TWD, while our model-based Fair Value estimate is 48.50 TWD — implying the stock looks roughly 2.4% overvalued today. We read business quality at 87/100 (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: medium).
About the company
Tachia Yung Ho Machine Industry Co., Ltd. engages in the manufacture and sale of butt-welding pipe fittings and high purity components in Taiwan. It offers butt-welding pipe fittings, such as elbows, tees, reducers, caps, stub ends, etc.; and UHP components, including high purity pipes and pipe fittings, metal gasket face seal fittings, micro butt-welding fittings, lok-DJR compression fittings, UHP CGA/DISS fittings, high purity ball valves, VMB/VMP systems, special chemical storage tank, equipment welding assembly, precision parts processing, electrolytic polishing, and OEM/ODM products. The company's butt-welding pipe fittings are used in the areas of petrochemical, ship building, food, sugar making, paper production, chemical engineering, agricultural chemical, dyeing, synthetic fibers, liquid chemical, gas, industries piping, construction drainage pipe fitting, etc.; and UHP components have applications in the areas of semiconductor, LCD-TFT, solar energy, LED, food industry, ch…
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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.