Ming Yang Smart Energy Group (601615) Fair Value & Analysis
Industrials · CN · Market cap 27.5B CNY
Analysis
Ming Yang Smart Energy Group (601615) currently trades at ¥12.61, while our model-based Fair Value estimate is ¥7.80 — implying the stock looks roughly 38.1% overvalued today. We read business quality at 94/100 (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
Ming Yang Smart Energy Group Limited engages in the research and development, design, manufacture, sale, maintenance, and operation of energy equipment, wind turbines, and core components in China. It offers onshore and offshore wind turbines; manufactures fan blades; offshore wind power technology; sells platforms; wind power equipment; wind power project investment; photovoltaic products; energy project development; develops and operates wind power; power generation and electricity sales; technology development and service; engineering design and construction; and software and technical services. The company also offers blades, gearboxes, inverter systems, control systems, booster systems, and flexible DC output systems; and floating offshore wind platforms, and integrated solutions for wind, solar, storage, hydrogen, and gas. Ming Yang Smart Energy Group Limited was founded in 2006 and is based in Zhongshan, China.
Open the full interactive analysis →
Similar stocks
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.