Taiwan Takisawa Technology Co (6609) Fair Value & Analysis
Technology · TW · Market cap 3.0B TWD
Fair value as of: Jun 25, 2026
Analysis
Taiwan Takisawa Technology Co (6609) currently trades at 41.45 TWD, while our model-based Fair Value estimate is 14.26 TWD — implying the stock looks roughly 65.6% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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
Taiwan Takisawa Technology Co., Ltd. engages in the manufacturing and sales of mechanical equipment, and other electric and electronic machinery in Asia, Europe, the United States, and internationally. The company offers single turret CNC horizontal lathe, horizontal turning center with milling, and horizontal turning center with Y-Axis; multi-turret horizontal turning center; vertical lathe; inverted vertical turning center; mill turn center; ultra precision lathe; digital high speed meticulous drilling machine; automation products; intelligent functions; intelligent software; and large CNC horizontal lathe. It also provides machine tools, such as small and medium CNC lathes, and non-CNC high speed precision lathes. The company serves bicycle, motorcycle, and automobile industries, as well as parts processing plants supplying the aeronautic industry. The company was founded in 1960 and is headquartered in Taoyuan 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.