Okong Corporation (045060) Fair Value & Analysis
Basic Materials · KR · Market cap 34.1B KRW
Fair value as of: Jun 25, 2026
Analysis
Okong Corporation (045060) currently trades at 2,135 KRW, while our model-based Fair Value estimate is 4,677 KRW — implying the stock looks roughly 119.1% undervalued today. We read business quality at 94/100 (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
Okong Corporation engages in the manufacture and sale of various adhesives in South Korea and internationally. The company offers water-based adhesives for wooden plywood/interior, paper craft, glued laminated timber, PVC sheet, paper, laminating paper, packaging, cigarette, flame retardant binder, and mortar binder works, as well as woodworking; and solvent-based adhesives for rubber-based adhesive, spray type, synthetic resins, and insulator works. It also provides hot melt sticks, packaging hot melt, hot melt for car, and other hot melts; sealants, including construction silicon sealants, silicon sealant for electrical and electronic use, bath interior silicone sealants, tubular sealants, acrylic sealants, butyl sealants, and multipurpose sealants; ceramic tile adhesives, such as interior tile, powder tile, and epoxy adhesives; PVC flooring adhesives; and other adhesives comprising PU foam, wax/compound, and super glue. In addition, the company offers packaging products, includin…
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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.