Yangzhou Seashine New Materials Co (300885) Fair Value & Analysis
Industrials · CN · Market cap 6.4B CNY
Fair value as of: Jun 24, 2026
Analysis
Yangzhou Seashine New Materials Co (300885) currently trades at ¥25.66, while our model-based Fair Value estimate is ¥4.67 — implying the stock looks roughly 81.8% overvalued today. We read business quality at 89/100 (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
Yangzhou Seashine New Materials Co., Ltd., together with its subsidiaries, engages in the research, development, production, and sale of powder metallurgy products in China and internationally. It offers power tool parts, including gears, bearings, structural components, and gearboxes; and automotive parts, such as CVVL systems, engine inner and outer rotors, mechanical vacuum pumps, oil pump rotors, gear hubs, sprockets, shock absorbers, charging guns, scroll wheel knobs, brake friction pads, and oil-impregnated bearings, as well as drive, electronic handbrake, electric drive shaft, and input gears. The company also provides home appliance parts comprising valve seats, uninstallers, positioning circles, and counterweight products; one-way bearings; front and back panels; magnetic rings; shuttles; and gearbox rotor assembly. In addition, it is involved in manufacturing and sale of core radio frequency components and related modules; technical services; wholesale trade; and investmen…
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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.