Ningbo Cixing Co (300307) Fair Value & Analysis
Industrials · CN · Market cap 6.7B CNY
Analysis
Ningbo Cixing Co (300307) currently trades at ¥7.97, while our model-based Fair Value estimate is ¥2.90 — implying the stock looks roughly 63.6% 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 Cixing Co.,Ltd. engages in the research, development, production, and sale of knitting machinery in China and internationally. It operates through Flat Knitting Machine Business, Mobile Internet Business, Automation Equipment and Project Integration Business, and Other Businesses segments. The company offers intelligent knitting machinery and equipment; flat knitting machines, steiger, circular machines, and other smart knitting equipment; and computerized shoe machines, automated shoe-making production lines, automatic ironing machines, and industrial robots. It also provides pre-sales, sales, after-sales, and technical support services; and mobile internet services, which include online reading and e-commerce promotion services. In addition, the company engages in the sale of textile machinery, textile machinery software, and textile machinery spare parts; personalized customization and design of textiles, apparel, and footwear based on the Internet of Things; and informati…
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.