Yanpai Filtration Technology Co (301081) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 3.6B CNY
Analysis
Yanpai Filtration Technology Co (301081) currently trades at ¥14.71, while our model-based Fair Value estimate is ¥1.63 — implying the stock looks roughly 88.9% 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: medium).
About the company
Yanpai Filtration Technology Co., Ltd. engages in the research, development, production, and sale of filter materials in China and internationally. It offers needle punched felt products comprising dust bags, such as PTFE polytetrafluoroethylene, GL glass fiber, PPS polyphenylene sulfide, MX Aramid, PI polyimide, DT acrylic, and PR polyester filter bags, as well as glass fiber composite felt filter materials and micron filter felts; woven filter cloths; filter belt/dry products consisting of pressing, sludge dewatering, vacuum drying, material conveying, and desulfurization; air slides, such as breathable layer cloths; and synthetic fibers. Its products are used in industrial dust removal, wastewater treatment, industrial production filtration and purification in thermal power, cement, chemical, metallurgy, mining, waste incineration, food, medicine, environmental protection, and new energy and other industries. The company was incorporated in 2014 and is headquartered in Tiantai, C…
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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.