Huvis Corporation (079980) Fair Value & Analysis
Consumer Cyclical · KR · Market cap 65.6B KRW
Fair value as of: Jun 24, 2026
Analysis
Huvis Corporation (079980) currently trades at 1,825 KRW, while our model-based Fair Value estimate is 3,397 KRW — implying the stock looks roughly 86.1% undervalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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
Huvis Corporation develops, manufactures, and sells chemicals fiber materials in South Korea and internationally. The company offers staple fibers for use in automobile, bedding/furniture, sanitary product, construction, agriculture, clothing, and ecofriendly products; long fiber for clothing, functional/sportswear, interior/industrial, and eco products; PET resins for fibers, films, and food and beverage containers; and meta-aramid and polyphenylene sulfide fibers for firefighting suits and safety suits, industrial filters, automotive applications, and construction materials. It also provides non-woven, high tenacity yarn, spunbond, geogrid, and monofilament industrial materials that are used in various areas comprising industrial, consumer, civil engineering/construction, and sanitary applications. In addition, the company offers PET foam and elastic nonwoven fabric. Huvis Corporation was founded in 2000 and is headquartered in Seoul, South Korea.
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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.