Tianjin Yiyi Hygiene Products Co (001206) Fair Value & Analysis
Consumer Defensive · CN · Market cap 3.2B CNY
Fair value as of: Jun 25, 2026
Analysis
Tianjin Yiyi Hygiene Products Co (001206) currently trades at ¥16.85, while our model-based Fair Value estimate is ¥20.79 — implying the stock looks roughly 23.4% undervalued today. We read business quality at 95/100 (high quality), in the Consumer Defensive sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Tianjin Yiyi Hygiene Products Co.,Ltd, together with its subsidiaries, engages in the research, development, production, and sale of disposable hygiene products and non-woven fabrics in China and internationally. The company offers pet and personal hygiene care products, including pet pads, pet diapers, pet cleaning bags, pet wipes, and pet garbage bags, etc.; and personal hygiene care products comprising sanitary napkins, nursing pads, and diapers, etc. It also engages in the wholesale and retail of pet food and supplies. The company offers its products under the HUSHPET and Yiping Flower Shop brands. It serves large-scale chain retailers, professional pet supply chain stores, and online pet supply sales platforms. The company exports its products to approximately 40 countries and regions, including the United States, Japan, South Korea, Canada, Italy, and the United Kingdom. Tianjin Yiyi Hygiene Products Co.,Ltd was founded in 1990 and is based in Tianjin, China.
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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.