Ningbo Donly Co (002164) Fair Value & Analysis
Industrials · CN · Market cap 7.0B CNY
Analysis
Ningbo Donly Co (002164) currently trades at ¥12.92, while our model-based Fair Value estimate is ¥5.52 — implying the stock looks roughly 57.3% 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: high).
About the company
Ningbo Donly Co.,Ltd engages in the research and development, manufacture, sale, and technical consultation of transmission equipment, door control systems, and industrial automatic control systems in China and internationally. It offers special, non-standard, and standard gears used in metallurgy, mining, environmental protection, construction, electricity, water conservancy, and other industries; electric drive equipment, including motors and special motors used in metallurgy, starting, roller table, frequency conversion, braking, construction, and other industries; and automatic door control systems, such as automatic doors for operating rooms, passages, radiation protection, and wards, as well as emergency evacuation doors, automatic overlapping doors, and other automatic door control devices for use in hospitals, pharmaceutical companies, office buildings, and other industries. Ningbo Donly Co.,Ltd was formerly known as Ningbo Donly Transmission Equipment Co., Ltd. and changed …
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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.