Ta Liang Technology Co (3167) Fair Value & Analysis
Industrials · TW · Market cap 72.2B TWD
Analysis
Ta Liang Technology Co (3167) currently trades at 793.00 TWD, while our model-based Fair Value estimate is 125.13 TWD — implying the stock looks roughly 84.2% overvalued today. We read business quality at 95/100 (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
Ta Liang Technology Co., Ltd. engages in the manufacture and sale of semiconductor inspection products, PCB routing and drilling machines, resin panel cutters, CNC engraving and milling machines, and glass panel processing machines. The company provides PCB routing machines for various applications, including optical modules, mini LED, semiconductor fixtures, mobile phone rigid PCBs, rigid-flex PCBs, and BGA substrates; and PCB drilling machines for AI servo PCB, communication PCB, satellite communication PCB, and vehicle PCB applications. It also offers film plotters; automated edge coating machines; and metrology series, AOI series-wafer level/panel level package, AOI series-die level package, and automation series products. In addition, the company provides FOUP/FOSB automatic optical inspection, wafer micro defects/macro defects automatic optical inspection, and wafer sorter equipment; and UWB positioning/data transmission systems. It has operations in Taiwan, Mainland China, Vi…
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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.