China Leadshine Technology Co (002979) Fair Value & Analysis
Industrials · CN · Market cap 16.7B CNY
Analysis
China Leadshine Technology Co (002979) currently trades at ¥53.43, while our model-based Fair Value estimate is ¥13.99 — implying the stock looks roughly 73.8% overvalued today. We read business quality at 94/100 (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
China Leadshine Technology Co., Ltd., together with its subsidiaries, provides motion control products and solutions in China and internationally. It operates in three segments: Drive Division, Control Division, and Motor Division. The company offers fieldbus products comprising EtherCAT, EtherNet/IP, CANopen, and Modbus RTU; integrated stepper motors and closed loops, stepper motors, and integrated server motors; stepper drives; and closed loop stepper motors and stepper drives. It also provides controls, such as remote I/O modules, PLCs, and HMIs; motor, encoder, brake, tuning, and communication cables; power supplies and gearboxes; and technical support services. In addition, the company is involved in trading; software development; venture capital; industrial automation products; robot joint module solutions; and dexterous hand solutions. It serves the CNC machinery and laser, and electronics industries; and the 3C manufacturing equipment, semiconductor equipment, robots, PCB/PC…
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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.