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Shenzhen CDL Precision Technology Co (300686) Fair Value & Analysis

Technology · CN · Market cap 5.1B CNY

Price¥20.04
Fair Value¥9.29
Upside-53.6%
Quality95/100
Evidence: Low Range ¥6.97 – ¥11.61

Analysis

Shenzhen CDL Precision Technology Co (300686) currently trades at ¥20.04, while our model-based Fair Value estimate is ¥9.29 — implying the stock looks roughly 53.6% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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

Shenzhen CDL Precision Technology Co., Ltd produces and sells functional basic components, structural devices, and optical components for consumer electronics in China. The company offers pasting and fixing functional devices, buffering and sealing functional devices, conductive and shielding functional devices, insulating functional devices, heat conduction and heat dissipation functional devices, and reinforcing and maintaining functional devices, as well as optical protective films, dustproof nets, labels, packaging boxes, composite sheet plate phone covers, flash covers, earpiece nets, etc. Its products are used in mobile phones, tablet computers, and communication digital products. Shenzhen CDL Precision Technology Co., Ltd was formerly known as CDL Sticky Products (Shen Zhen) CO.,LTD. and changed its name to Shenzhen CDL Precision Technology Co., Ltd. in 2013. The company was founded in 2004 and is based in Dongguan, China.

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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.