Wonik Cube Corp (014190) Fair Value & Analysis
Basic Materials · KR · Market cap 47.3B KRW
Fair value as of: Jun 24, 2026
Analysis
Wonik Cube Corp (014190) currently trades at 1,213 KRW, while our model-based Fair Value estimate is 1,664 KRW — implying the stock looks roughly 37.2% undervalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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
Wonik Cube Corp. distributes chemical, polymer, silicon, building, and printing and packaging materials in South Korea. It imports and sells basic chemicals, raw materials, etc. for paint, ink, adhesive, paper, artificial marble, electronic material, synthetic leather, and textile sectors. The company also supplies PC, PET, PETG, PMMA, and ULTEM products for use in electrical, electronic, automotive, medical, sheet, filament, and miscellaneous applications; and sells various silicon products, including momentive product fluids, silans, resins, and coatings that are used in applications, such as electronic, chemical fiber, construction, etc. In addition, it offers interior and exterior building materials; and sells digital printers, upgrading parts, and consumables, as well as provides training and technical support services. The company was formerly known as Hunus Inc. and changed its name to Wonik Cube Corp. in September 2013. Wonik Cube Corp. was founded in 1975 and is based in Se…
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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.