Chicony Power Technology Co (6412) Fair Value & Analysis
Industrials · TW · Market cap 36.8B TWD
Analysis
Chicony Power Technology Co (6412) currently trades at 93.10 TWD, while our model-based Fair Value estimate is 86.88 TWD — implying the stock looks roughly 6.7% 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
Chicony Power Technology Co., Ltd. engages in research, development, manufacturing, and trading of exchange-connected power supplies, electronic components and equipment, LED application products, and smart building systems in Taiwan, Asia, America, Europe, and internationally. It provides adapters, eSports PC, and EV energy conservation, as well as embedded PSUs for a range of industries, including server, cloud, data center, storage, and communications. The company also offers LED backlight modules and automotive lighting for various applications in laptop, PC, smartphone, 3C peripherals, and automotive fields. In addition, it provides magnetics components, such as transformers, PFC chokes, and line filters; and smart building management platforms. Further, it provides LED lighting modules, energy-saving technology consulting, and management services, as well as production and sales of specialized electronic equipment, power supplies, modular power supplies, magnetic components, c…
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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.