Fujian Septwolves Industry Co (002029) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 6.0B CNY
Fair value as of: Jun 25, 2026
Analysis
Fujian Septwolves Industry Co (002029) currently trades at ¥8.39, while our model-based Fair Value estimate is ¥7.62 — implying the stock looks roughly 9.2% overvalued today. We read business quality at 94/100 (high quality), in the Consumer Cyclical 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
Fujian Septwolves Industry Co., Ltd. engages in the research and development, design, manufacturing, and sales of clothing and apparel products and raw material in China and internationally. The company offers men's shirts, suits, trousers, jackets, sweaters, underwear, briefs, socks, and other knitting products under the Seven Wolves brand name. It is involved in embroidery and printing processing, property management, and house rental operations; sales training and consulting activities; interior decoration business; general merchandise; department store sales; and foreign trade and venture capital. In addition, the company provides building materials; computer software and hardware services; and hardware and electrical appliances. It sells its products through franchise stores and online. The company was formerly known as Fujian Septwolves Garment Industry Co., Ltd. and changed its name to Fujian Septwolves Industry Co., Ltd. in July 2001. The company was founded in 1989 and is b…
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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.