Shenzhen Zhongjin Lingnan Nonfemet Co (000060) Fair Value & Analysis
Basic Materials · CN · Market cap 35.2B CNY
Analysis
Shenzhen Zhongjin Lingnan Nonfemet Co (000060) currently trades at ¥8.81, while our model-based Fair Value estimate is ¥3.43 — implying the stock looks roughly 61.1% overvalued today. We read business quality at 92/100 (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
Shenzhen Zhongjin Lingnan Nonfemet Co. Ltd., together with its subsidiaries, engages in the mining, beneficiation, and smelting of non-ferrous metals in China and internationally. Its product portfolio includes lead and zinc concentrates, copper concentrates, lead ingots, zinc ingots and alloys, cathode copper, silver, gold, cadmium ingots, germanium ingots, indium ingots, industrial sulfuric acid, sulfur, and other products. The company is also involved in the trade of non-ferrous metals, such as lead and zinc, cathode copper, silver, and other metals, as well as the recovery of gold, silver, gallium, germanium, and indium. In addition, the company offers aluminum profiles, aluminum doors and windows, battery zinc powder, flaky zinc powder, perforated nickel-plated steel strips, composite metal materials and bimetallic components, and electrical contact materials and components. Further, it engages in sales of intelligent basic manufacturing equipment; investment activities; proper…
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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.