Dongguan Chitwing Technology Co (002855) Fair Value & Analysis
Industrials · CN · Market cap 2.8B CNY
Fair value as of: Jun 25, 2026
Analysis
Dongguan Chitwing Technology Co (002855) currently trades at ¥10.42, while our model-based Fair Value estimate is ¥2.21 — implying the stock looks roughly 78.8% overvalued today. We read business quality at 93/100 (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: low).
About the company
Dongguan Chitwing Technology Co., Ltd., together with its subsidiaries, engages in the research, design, development, manufacturing, and sale of precision molds, precision structural parts, and hardware components in China and internationally. The company offers precision structural parts, including wireless chargers, wireless leather case keyboards, smart home components, high-precision connectors, cameras, and other precision parts. It also provides injection molding, painting, plating, silk screen printing, assembly, laser engraving, continuous strip-type masking sandblasting, high-speed precision stamping, precision continuous forging, and others. In addition, the company is involved in the provision of equipment heat dissipation technology solutions; software and IT services; technology development; and trading and investing activities. Its products are used in mobile phones, tablet computers, smart wearable devices, and smart terminals, as well as medical equipment, automotive…
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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.