Guangdong Shenling Environmental Systems Co (301018) Fair Value & Analysis
Industrials · CN · Market cap 41.2B CNY
Analysis
Guangdong Shenling Environmental Systems Co (301018) currently trades at ¥109.90, while our model-based Fair Value estimate is ¥12.16 — implying the stock looks roughly 88.9% overvalued today. We read business quality at 95/100 (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
Guangdong Shenling Environmental Systems Co., Ltd. research, develops, designs, manufactures, and markets air conditioning equipment in China and internationally. It offers industrial and special, as well as public and commercial air conditioning units for industrial and research process, public and commercial buildings, and other applications. In addition, the company offers data service products, such as cloud data and computing centers, communication infrastructure, computer technology services, precision electronic instrument production, and other fields. The company serves power grids, chemical, metallurgy, food and beverages, pharmaceuticals, machinery and equipment, cement, automobiles, railways, subways, airports, nuclear power, aerospace, environmental management, hospitals, military, defense, and other sectors. Guangdong Shenling Environmental Systems Co., Ltd. was founded in 2000 and is headquartered 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.