Aethertek technology co., Ltd (3219) Fair Value & Analysis
Industrials · TW · Market cap 5.4B TWD
Fair value as of: Jun 24, 2026
Analysis
Aethertek technology co., Ltd (3219) currently trades at 72.00 TWD, while our model-based Fair Value estimate is 39.09 TWD — implying the stock looks roughly 45.7% overvalued today. We read business quality at 80/100 (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: medium).
About the company
Aethertek technology co., Ltd., together with its subsidiaries, manufactures and sells precision testing equipment for the consumer and automotive electronics, and AI server testing industries in Taiwan and China. It offers RF test products comprising up-down converters, RF switches, shield boxes, and passive antennas; board level tests; microprobe products, including sockets and board-to-board POGO blocks; and antenna-in-module, and antenna test and calibration products for 5G applications. The company's products provide functional test, device firm upgrade, radio frequency test, and product assembly test solutions for consumer electronics; reliability, function, and radio frequency test solutions for automotive electronics; in-circuit, board function, and boundary scan interconnect test solutions for servers; product system integration solutions for automation applications; and signaling and non-signaling test solutions for MMWAVE applications, as well as offers antenna, software,…
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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.