Zhongzhong Science & Technology (Tianjin) Co (603135) Fair Value & Analysis
Industrials · CN · Market cap 7.9B CNY
Analysis
Zhongzhong Science & Technology (Tianjin) Co (603135) currently trades at ¥12.75, while our model-based Fair Value estimate is ¥2.79 — implying the stock looks roughly 78.1% 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
Zhongzhong Science & Technology (Tianjin) Co., Ltd. manufactures and supplies metallurgical equipment in China and internationally. Its products include hot rolled strip, section, bar/wire, and plate mills; cold rolled strips mills; and EAF and LF products, continuous casting machines, and wheels production lines, as well as pickling, galvanizing, and coating services. The company also offers electric drive and automation, hydraulic and lubrication, water treatment, and dedusting systems; reheating furnace, and H/L voltage distribution and SVG solutions; and spare parts, such as hydraulic cylinders, bearing chocks, cardan shafts, reducers and gears, gear motors, and other machined parts. In addition, it provides individual equipment, including rolling mills, flying shears, straighteners, saws, cooling beds, collecting devices, coilers, automatic bundlers, and roller table and other equipment. The company was founded in 2001 and is based in Tianjin, 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.