Tae Kwang Corporation (023160) Fair Value & Analysis
Industrials · KR · Market cap 762B KRW
Fair value as of: Jun 24, 2026
Analysis
Tae Kwang Corporation (023160) currently trades at 26,600 KRW, while our model-based Fair Value estimate is 25,470 KRW — implying the stock looks roughly 4.2% overvalued today. We read business quality at 86/100 (high quality), in the Industrials 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
Tae Kwang Corporation manufactures, supplies, and sells butt weld pipe fittings for oil and gas, chemical and petrochemical, power plant, and shipbuilding businesses in Korea and internationally. The company offers butt-welding fittings, including carbon, stainless, and alloy steel, such as elbows, tees, reducers, caps, stub ends, laterals, long bends, and crosses, as well as special, jacket, and split fittings; and forged fittings, such as carbon, stainless, and alloy steel comprises elbows, tees, reducers, sockets, couplings, bosses, crosses, caps, outlets, plugs, unions, inserts, nipples, swage nipples, and special items. It also provides flange fittings comprising carbon, stainless, and alloy steel, which include slip-ons, welding necks, threads, socket weldings, blinds, long welding necks, lap joints, grooves, and nozzle necks. The company was formerly known as Taekwang Bend Industry Company and changed its name to Tae Kwang Corporation in March 2001. Tae Kwang Corporation was …
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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.