Shareate Tools Ltd (688257) Fair Value & Analysis
Industrials · CN · Market cap 28.5B CNY
Analysis
Shareate Tools Ltd (688257) currently trades at ¥111.80, while our model-based Fair Value estimate is ¥14.02 — implying the stock looks roughly 87.5% overvalued today. We read business quality at 88/100 (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
Shareate Tools Ltd. engages in the research, development, production, and sales of cemented carbide and drilling tools in China and internationally. The company offers mining tri-cone drill bit and water well bits; DTH hammer and bit; horizontal directional drilling products comprises reamers and single roller cone bit; core barrel roller bit; raise bore tools; and top hammer drilling tools. It also provides mining tungsten carbide products, including tungsten carbide button, carbide substrate, shield machine tool, coal cutter pick, and tungsten carbide tubular electrode; precision components; cutting tools such as carbide rod and inserts, and round tools; tungsten carbide die products comprising carbide plates, cold headings, hobs, and powder metallurgy dies; and cermet products. The company was formerly known as Kingdream Shareate Tools Ltd. and changed its name to Shareate Tools Ltd. in May 2012. Shareate Tools Ltd. was founded in 1973 and is headquartered in Suzhou, China.
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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.