Guangdong Construction Engineering Group (002060) Fair Value & Analysis
Industrials · CN · Market cap 12.3B CNY
Analysis
Guangdong Construction Engineering Group (002060) currently trades at ¥3.20, while our model-based Fair Value estimate is ¥6.20 — implying the stock looks roughly 93.8% undervalued today. We read business quality at 94/100 (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
Guangdong Construction Engineering Group Co., Ltd. operates in the civil engineering and construction industry in China. The company engages in the water conservancy and hydropower facilities, municipal public works, highway projects, mechanical and electrical installation projects, foundation projects, and housing projects. It is also involved in the engineering construction business, such as construction projects, hydropower, wind power, solar energy, and other power generation businesses; steel structure fabrication and installation; architectural decoration and renovation; survey and design, construction, operation, and maintenance of supporting facilities; electricity and heat production and supply; and renewable energy. The company was formerly known as Guangdong No.2 Hydropower Engineering Company, Ltd. and changed its name to Guangdong Construction Engineering Group Co., Ltd. in February 2024. Guangdong Construction Engineering was incorporated in 2001 and is based in Guangz…
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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.