Jiangsu Huaxicun Co (000936) Fair Value & Analysis
Basic Materials · CN · Market cap 5.2B CNY
Analysis
Jiangsu Huaxicun Co (000936) currently trades at ¥5.84, while our model-based Fair Value estimate is ¥2.54 — implying the stock looks roughly 56.5% overvalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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
Jiangsu Huaxicun Co.,Ltd. engages in the research and development, production, and sale of polyester chemical fibers in China and internationally. The company offers polyester staple fibers for spunlace for use in spunlace, acupuncture, and other equipment, as well as hygiene materials, medical treatment and wiping, automobiles, filtration, leather, and engineering infrastructure; and semi-dull polyester staple fibers, bright polyester staple fibers, fluorescent whitening polyester staple fibers, etc. for use in textile industry, as well as fibers of needle punching and chemical bonding specifications, which are used in various fields, such as pure spinning, blended spinning, spunlace, and knitting. It also provides petrochemical logistics and warehousing services, such as terminal loading and unloading, warehousing, transshipment, pipeline transportation and other services. In addition, the company involved in the construction, operation, warehousing, and support service of wharf; …
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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.