SNT Holdings (036530) Fair Value & Analysis
Industrials · KR · Market cap 760B KRW
Fair value as of: Jun 26, 2026
Analysis
SNT Holdings (036530) currently trades at 49,350 KRW, while our model-based Fair Value estimate is 98,700 KRW — implying the stock looks roughly 100.0% undervalued today. We read business quality at 80/100 (high quality), in the Industrials 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: medium) — always confirm before acting.
About the company
SNT Holdings Co., Ltd. engages in manufacturing and selling automobile parts and industrial facilities businesses. It offers auto parts, defense products, semiconductor equipment and materials; precision machine tools and medium-large sized casting products; axle systems; and machine tools. It also offers air coolers, heat recovery steam generators, condensers, and SCR systems for petrochemical refineries, gas plants, and generating stations. The company also operates a savings bank that provides various banking and financial products; and operates a hotel business. In addition, it develops, operates, and manages information systems and offers solutions in the fields of total outsourcing, ERP, POP, PLM, SCM, etc. The company was formerly known as S&T Holdings Co., Ltd. and changed its name to SNT Holdings Co., Ltd. in February 2021. SNT Holdings Co., Ltd. was founded in 1979 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.