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China Nuclear Engineering Corporation (601611) Fair Value & Analysis

Industrials · CN · Market cap 32.3B CNY

Price¥11.16
Fair Value¥8.70
Upside-22.0%
Quality84/100
Evidence: Medium Range ¥7.03 – ¥9.90

Analysis

China Nuclear Engineering Corporation (601611) currently trades at ¥11.16, while our model-based Fair Value estimate is ¥8.70 — implying the stock looks roughly 22.0% overvalued today. We read business quality at 84/100 (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: medium).

About the company

China Nuclear Engineering Corporation Limited engages in the nuclear power, industrial, and civil engineering businesses in China and internationally. It is involved in the construction of nuclear power plants, high temperature reactors, heavy water reactors, experimental fast reactors, advanced research reactors, etc.; system engineering construction projects in the fields of nuclear industry, aerospace, aviation, shipbuilding, etc.; and industrial and civil engineering construction services, which covers housing construction, municipal administration, highways, bridges, tunnels, environmental protection, urban rail, petrochemical, water conservancy and hydropower construction, etc. The company was founded in 2010 and is headquartered in Shanghai, China. China Nuclear Engineering Corporation Limited operates as a subsidiary of China National Nuclear Corporation.

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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.