Kunshan Kersen Science & Technology Co (603626) Fair Value & Analysis
Industrials · CN · Market cap 12.2B CNY
Fair value as of: Jun 24, 2026
Analysis
Kunshan Kersen Science & Technology Co (603626) currently trades at ¥20.84, while our model-based Fair Value estimate is ¥2.64 — implying the stock looks roughly 87.3% 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: medium).
About the company
Kunshan Kersen Science & Technology Co.,Ltd. researches, develops, manufactures, sells, and services precision structural parts. The company also engages in precision die casting, forging, stamping, CNC, laser cutting, laser welding, MIM, precision injection molding. In addition, the company offers consumer electronics products including shells, middle frames, middle plates, buttons, logos, and shaft (hinge) assemblies for terminal products such as smartphones, laptops, tablets, smart wearables, smart speakers, heat-not-burn electronic cigarette structural parts, and VR; medical device products include structural cigarette parts required for terminal products such as scalpels, bone screws, and pacemakers; energy storage products are mainly PACK module products; and automobiles, including new energy vehicles for well-known international and domestic customers such as Apple, Huawei, Amazon, Google, Meta, and Medtronic. The company was founded in 2003 and is based in Kunshan, 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.