Daesung Hi-Tech Co (129920) Fair Value & Analysis
Industrials · KR · Market cap 80.6B KRW
Fair value as of: Jun 24, 2026
Analysis
Daesung Hi-Tech Co (129920) currently trades at 4,965 KRW, while our model-based Fair Value estimate is 8,425 KRW — implying the stock looks roughly 69.7% undervalued today. We read business quality at 94/100 (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: low) — always confirm before acting.
About the company
Daesung Hi-Tech Co., Ltd. manufactures and sells precision parts for various industrial machines in South Korea and internationally. The company offers precision components, such as spindles, spindle unit, index couplings, collets, worm and seal shafts, gears, spacers, tool holders, sleeves, housings, manifold blocks, ATC arms, magnet plates, bearings, scrolls, impellers, brackets, valves, universal joints, auto lathe samples, mso coils, mobile jigs, and ceramics. It also provides compact machining centers for machining electric vehicle battery cases, motors, and module parts; Swiss-turn automatic lathes; and organic rankine cycle waste heat recovery power generation products under the Thermapower brand. In addition, the company offers metal cutting and hobbing machines; various IT parts, such as foldable hinges, etc.; and semiconductor equipment. It exports its products to the United States, Japan, and Germany. The company was founded in 1995 and is headquartered in Daegu, South Ko…
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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.