Jiangsu Alcha Aluminium Group (002160) Fair Value & Analysis
Basic Materials · CN · Market cap 4.7B CNY
Analysis
Jiangsu Alcha Aluminium Group (002160) currently trades at ¥4.44, while our model-based Fair Value estimate is ¥1.34 — implying the stock looks roughly 69.8% overvalued today. We read business quality at 95/100 (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
Jiangsu Alcha Aluminium Group Co., Ltd. provides industrial heat transfer materials, heat transfer equipment, and comprehensive solutions in China and internationally. It offers automotive/industrial heat treatment and heat transfer system solutions, such as cooling systems, thermal and sound insulation materials, car air conditioning systems, battery cooling systems, and automobile power battery shells; new energy products comprising lithium-ion batteries and water-cooling plates; conditioning heat exchange solutions, such as light foils and hydrophilic coated aluminum foils; and clean energy solutions that include design consulting services, clean engineering services, clean industrial equipment, and clean engineering materials. The company was formerly known as Jiangsu Alcha Aluminium Co.,Ltd. and changed its name to Jiangsu Alcha Aluminium Group Co., Ltd. in May 2019. Jiangsu Alcha Aluminium Group Co., Ltd. was founded in 1987 and is headquartered in Changshu, 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.