ShenZhen Woer Heat-Shrinkable Material Co (002130) Fair Value & Analysis
Industrials · CN · Market cap 28.7B CNY
Analysis
ShenZhen Woer Heat-Shrinkable Material Co (002130) currently trades at ¥20.44, while our model-based Fair Value estimate is ¥18.92 — implying the stock looks roughly 7.4% 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
ShenZhen Woer Heat-Shrinkable Material Co.,Ltd., together with its subsidiaries, provides electrical and mechanical insulations solutions in China and internationally. It operates through five segments: Electronic Materials, Communication Cables, Power, New Energy, and Wind Power Generation. The company offers heat shrinkable sleeves, busbar tubes, and cable accessories; cable branch boxes; ring network cabinets; high and low voltage switchgears; WQFB fully insulated closed busbar tubes; environmentally friendly high temperature silicone wires; high-temperature resistant PTFE casings; conductor connecting pipes; heat shrinkable composite double-wall pipes; silicone rubber pipes; PTFE casings; civil anti-skid pattern tubes; halogen-free environmentally friendly PE cross-linked wires, etc. It also provides dual and single wall, wire and pipeline protection, and wire and cable identification products; heat and cold shrink cable accessories; separable connectors mated products, accessor…
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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.