Chang Lan Technology Group (002879) Fair Value & Analysis
Industrials · CN · Market cap 2.8B CNY
Fair value as of: Jun 25, 2026
Analysis
Chang Lan Technology Group (002879) currently trades at ¥14.44, while our model-based Fair Value estimate is ¥14.55 — implying the stock looks roughly 0.8% undervalued today. We read business quality at 83/100 (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
Chang Lan Technology Group Co., Ltd. engages in the research and development, production, sale, and service of power cable accessories and supporting products in China and internationally. It offers AC and DC cable accessories; power cable accessories, power equipment, electrical materials, intelligent online monitoring, electromechanical facilities, and transformer insulating oil, etc.; ultra-high voltage and high voltage cable accessories, medium and low voltage cable accessories, power fittings, electrical equipment, and complete cable laying equipment; and electrical materials, online monitoring platforms for power equipment, mineral insulating oil, natural ester insulating oil, and synthetic ester insulating oil. The company also provides cable terminals and connectors; auxiliary materials; pre mold cable accessories; separable elbow connector; grounding device; and tools for installation and cable laying. The company's products are used in power grid, power plant, subway, new …
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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.