KNR System Inc (199430) Fair Value & Analysis
Industrials · KR · Market cap 162B KRW
Fair value as of: Jun 24, 2026
Analysis
KNR System Inc (199430) currently trades at 12,570 KRW, while our model-based Fair Value estimate is 9,467 KRW — implying the stock looks roughly 24.7% overvalued today. We read business quality at 95/100 (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: low).
About the company
KNR System Inc. provides robotics, test equipment, and testing services in South Korea and internationally. The company offers teleoperated hydraulic robot for steelworks, continuous casting nozzle changing, fluidized bed furnace nozzle and duct cleaning, underwater sticky sludge cleaning, and pipe inspection and cleaning robots for steel and chemistry sector; fallen coal retrieval, nuclear fusion reactor remote handling, nuclear power plant decommissioning, cooling water intake dredging, and nuclear fuel rod retrieval robots for electric power and energy plants sector; nuclear fuel rod retrieval robot, ship simulation module robot arm, ship painting mobile robot, and automated ship mooring system for shipbuilding and marine sector; and tunnel rock bolt construction automation robot and silent tunnel excavation robot system for construction and civil engineering sector. It also provides components for defense wearable robots, high-precision satellite thruster valve, and automated bl…
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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.