Jiangsu Chint Power Technology Co (002150) Fair Value & Analysis
Industrials · CN · Market cap 176B KRW
Analysis
Jiangsu Chint Power Technology Co (002150) currently trades at 4,855 KRW, while our model-based Fair Value estimate is 5,584 KRW — implying the stock looks roughly 15.0% undervalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.
About the company
Jiangsu Chint Power Technology Co., Ltd. engages in the research and development, production, and sale of photovoltaic energy storage equipment, components, and metal products in China. It offers tool cabinets, tool boxes, workbenches, tool carts, garages, workshops, and tool plates; IT cabinets, junction boxes, outdoor IT cabinets, high- and low-voltage switchgears, explosion-proof products, and safety protection products; electrical control boxes; outdoor TVs; outdoor display products; monitoring equipment; medical-grade touch-screen fridges and integrated control cabinets; and precision sheet metals comprising servers, beverage machines, medical sheet metal products, self-service equipment, coffee machines, Siemens door panels, and other sheet metal products. The company also provides laptop/Chromebook computer charging carts, file cabinets, foldable kitchen island carts, rolling book carts, computer cabinets, and shelving units, as well as mini tillers. It exports its products. …
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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.