Gem-Year Industrial Co (601002) Fair Value & Analysis
Industrials · CN · Market cap 4.6B CNY
Analysis
Gem-Year Industrial Co (601002) currently trades at ¥4.62, while our model-based Fair Value estimate is ¥4.52 — implying the stock looks roughly 2.2% 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: high).
About the company
Gem-Year Industrial Co.,Ltd. engages in the research, development, production, and sale of fasteners and hardware tools in China, the United States, Japan, Europe, and internationally. The company offers fastener products, including general fasteners, as well as power, steel structure, home appliance, furniture, gypsum board, and car series. It also provides hardware tools, such as toolboxes, tool carts, and tool bags; sleeves and accessories; wrenches; electronic repair, mechanical elevator maintenance, and auto repair kits; and plier tools. In addition, the company offers bolts, nuts, screws, precision wires, and non-standard specialty fasteners; and tungsten carbide molds, railway fasteners, automated warehousing equipment, and rails. Further, it engages in warehousing and logistics; trading and distribution; and investment activities. The company's products are used in automobiles, high-speed rail, aviation, power, engineering machinery, bridges, construction, energy, and nuclea…
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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.