Mobiis Co (250060) Fair Value & Analysis
Technology · KR · Market cap 105B KRW
Fair value as of: Jun 24, 2026
Analysis
Mobiis Co (250060) currently trades at 2,805 KRW, while our model-based Fair Value estimate is 1,886 KRW — implying the stock looks roughly 32.8% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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
Mobiis Co., Ltd. designs and builds equipment and software for fusion reactors and particle accelerators worldwide. The company offers software engineering, such as software design, development and testing; V&V based on international quality standards; data acquisition and control; programming; distributed computing; data management and storage; visualization and user interface; simulation and modeling; machine learning and artificial intelligence; data analysis and process algorithm; and software testing and quality assurance services. It also provides integrated control systems, including industrial control; fast embedded control; and operating systems; bespoke instrumentation comprises customised hardware prototyping, design and development; beamline radio frequency instrumentation; beamline positioning and control instrumentation; and hardware manufacturing, testing, installation and maintenance; and mission critical systems that includes safety PLC technologies; hardwired inter…
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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.