Nanjing Canatal Data-Centre Environmental Tech Co (603912) Fair Value & Analysis
Industrials · CN · Market cap 4.6B CNY
Analysis
Nanjing Canatal Data-Centre Environmental Tech Co (603912) currently trades at ¥8.70, while our model-based Fair Value estimate is ¥14.85 — implying the stock looks roughly 70.7% 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: low) — always confirm before acting.
About the company
Nanjing Canatal Data-Centre Environmental Tech Co., Ltd provides digital infrastructure construction and energy management services in China and internationally. The company offers data center temperature control products, integrated modular data center solutions, energy management solutions, and precision air environment solution services. It also provides magnetic levitation water system solution, VRH heat pipe multi-connection waterless system solution, ECS integrated fluorinated pump solution, modular data center solution, container data center solution, distributed computing solution, cold station solution, C-IPM power module solution, cold plate liquid cooling solution, and immersion liquid cooling solutions. Nanjing Canatal Data-Centre Environmental Tech Co., Ltd serves education, hospital, business, hotel, finance, traffic, energy, war, communication, data center, and government sectors. The company was incorporated in 2003 and is headquartered in Nanjing, China.
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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.