Shanghai Smith Adhesive New Material Co (603683) Fair Value & Analysis
Basic Materials · CN · Market cap 9.0B CNY
Analysis
Shanghai Smith Adhesive New Material Co (603683) currently trades at ¥32.06, while our model-based Fair Value estimate is ¥5.21 — implying the stock looks roughly 83.7% overvalued today. We read business quality at 94/100 (high quality), in the Basic Materials 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: high).
About the company
Shanghai Smith Adhesive New Material Co.,Ltd manufactures and sells various adhesive tapes and adhesives in China. The company offers industrial materials, including masking, duct, rice paper, electronics, foam, aluminum foil, covering, double sided, and kraft paper tapes, as well as BOPP tapes; electronic materials, which comprise PET, blue film, transfer, conductive, PE foam, tissue, and fireproof paper tapes; and functional film materials, comprising anti-reflection, anti-glare, OCA optical, high temperature and polyurethane protective films, functional and antistatic AB glue. It also provides thermal management composites, which include synthetic graphite high thermal and graphene thermal conductive films; and specialty paper products, as well as solvent and waterborne acrylic pressure sensitive adhesives. The company offers its products under the Ginnva brand. Its products are used in consumer electronics, transportation, new energy battery, architectural decoration, smart medi…
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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.