Shantou Wanshun New Material Group (300057) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 9.3B CNY
Analysis
Shantou Wanshun New Material Group (300057) currently trades at ¥9.27, while our model-based Fair Value estimate is ¥15.14 — implying the stock looks roughly 63.3% undervalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.
About the company
Shantou Wanshun New Material Group Co., Ltd. engages in the paper packaging material, aluminum processing, and functional film businesses in China. The company products include transfer and composite papers used in cigarette labels, wine labels, daily chemicals, gifts, and other packaging fields; aluminum foil, aluminum strip, and carbon-coated foil are used in the fields of electronic components, such as batteries, capacitors, and printed circuit boards; packaging fields, including food, beverages, cigarettes, and medicine; daily use fields; and conductive films used in touch screen, dimming film/glass, and other fields. It also provides energy-saving membranes used in energy-saving fields comprising buildings and car films; high barrier films used in photovoltaic packaging, food and drug packaging, electronic device packaging, display packaging, and other fields; car coat films used in automobiles to protect the car paint; energy-saving films that are mainly used in energy-saving …
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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.