Kingboard Laminates Holdings (KGBLY) Fair Value & Analysis
Technology · US · Market cap $27.0B
Analysis
Kingboard Laminates Holdings (KGBLY) currently trades at $214.10, while our model-based Fair Value estimate is $29.53 — implying the stock looks roughly 86.2% 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: high).
About the company
Kingboard Laminates Holdings Limited, an investment holding company, engages in the manufacture and sale of laminates in the People's Republic of China, Europe, other Asian countries, and the United States. It operates through Laminates, Properties, and Investments segments. The company offers glass epoxy and paper laminates. It also provides upstream component materials, such as copper foils, glass yarns, glass fabrics, bleached kraft papers, epoxy resins, kraft papers for copper-clad laminates, and PVB. In addition, it sells and rents properties; trades in copper; and provides hotel accommodation services. Further, the company manufactures and distributes chemicals; electronic special materials; and specialty resins. Its investment property portfolio comprises commercial, residential, and industrial properties. The company was founded in 1988 and is headquartered in Sha Tin, Hong Kong. Kingboard Laminates Holdings Limited operates as a subsidiary of Jamplan (BVI) Limited.
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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.