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Grandblue Environment Co (600323) Fair Value & Analysis

Utilities · CN · Market cap 24.9B CNY

Price¥28.04
Fair Value¥33.29
Upside+18.7%
Quality86/100
Evidence: Medium Range ¥24.19 – ¥70.30

Analysis

Grandblue Environment Co (600323) currently trades at ¥28.04, while our model-based Fair Value estimate is ¥33.29 — implying the stock looks roughly 18.7% undervalued today. We read business quality at 86/100 (high quality), in the Utilities 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

Grandblue Environment Co., Ltd. engages in the water supply, drainage, solid waste treatment, and energy businesses in China. The company provides water intake, water production, water transmission, and drinking water services; and sewage treatment, and pipeline network operation and maintenance services, as well as manages and controls wastewater plants, draining pipeline networks, and pumping stations. It also engages in the waste incineration power generation, sludge disposal, fly ash disposal, ash landfill, waste landfill, solid waste environmental protection engineering, and sanitation; pipeline natural gas, bottled gas, hydrogen, and other multi-energy supply; and asset management businesses. Grandblue Environment Co., Ltd. was formerly known as Nanhai Development Co. Ltd. and changed its name to Grandblue Environment Co., Ltd. in December 2013. The company was founded in 1992 and is based in Foshan, 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.