Ta Yih Industrial Co (1521) Fair Value & Analysis
Consumer Cyclical · TW · Market cap 2.0B TWD
Fair value as of: Jun 24, 2026
Analysis
Ta Yih Industrial Co (1521) currently trades at 26.40 TWD, while our model-based Fair Value estimate is 16.09 TWD — implying the stock looks roughly 39.1% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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 Yih Industrial Co., Ltd. engages in the manufacturing and processing of automobile parts, motorcycle parts, rail vehicle parts, transportation machinery, and industrial plastic parts in Taiwan and internationally. It offers LED fishing lighting; and railway lighting, such as dimming controllers, rail vehicle luminaires interior lighting, LED boards, LED tubes, track lighting aluminum alloy parts, LED digital displays, reading lights, downlights, intelligent electronic ballast converters, indicator lights, side indicator lights, indicator lamps, flashing lights, tail lights, LED head lights, and HID PES headlamps for railway express. The company also provides passenger reading lights and light sensors; aerospace lighting, including high intensity searchlight, instrument night vision retrofit kit, ball transfer units, battery plastic cases, landing and taxi lights, dimmers, formation lights, position lights, and small lights; tail lamp, front turn signal lamp, and headlamp motorcyc…
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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.