CITIC Heavy Industries Co (601608) Fair Value & Analysis
Industrials · CN · Market cap 24.0B CNY
Analysis
CITIC Heavy Industries Co (601608) currently trades at ¥5.16, while our model-based Fair Value estimate is ¥1.72 — implying the stock looks roughly 66.7% overvalued today. We read business quality at 91/100 (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
CITIC Heavy Industries Co., Ltd. manufactures and sells heavy machinery in China and internationally. It operates in four segments: Mining and Heavy Equipment, Robotics and Intelligent Equipment, New Energy Equipment, and Special Materials. The company offers jaw crushers, hoist, gyratory and cone crushers, high pressure roller mill, vertical stirred mill, autogenous mill, semi-autogenous mill, ball mill, rod mill, vertical disc filter, anode furnace, and semi-mobile crushing station; rotary kiln, roller press, raw material vertical mill, equipment for new dry-cement production line, and slag grinding system; cantilever tunneling machine, vertical shaft, wind power rock-embedded drilling rig, and hard rock tunnel boring machine; and smelting anode, wide and thick plate rolling mill, steelmaking converter, pellet kiln, and straightening machine. It also provides vertical shaft drilling rig, multi-rope friction ground, electro-hydraulic transmission and control system, and double roll…
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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.