CLASSYS Inc (214150) Fair Value & Analysis
Healthcare · KR · Market cap 2.8T KRW
Analysis
CLASSYS Inc (214150) currently trades at 45,500 KRW, while our model-based Fair Value estimate is 21,836 KRW — implying the stock looks roughly 52.0% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare 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: high).
About the company
CLASSYS Inc. provides medical aesthetics devices worldwide. The company offers ULTRAFORMER MPT, a solution for eyebrow lifting; ULTRAFORMER III, an ultrasound surgical device used for tissue coagulation in eyelid lifting, and for skin tightening and improving subcutaneous tissue elasticity in the face (cheeks), abdomen, and thighs; VOLNEWMER, a monopolar radiofrequency therapeutic equipment used to coagulate skin tissue; Secret RF, a device that delivers radio frequency energy into the skin; Secret PRO, a multiple fractional device that delivers micro-level laser beams fractionally to the tissue; Secret DUO, a multi-functional device that delivers high-frequency energy through needle electrodes; and Fortra, a 4 wavelengths diode laser. It also provides SCIZER and CLATUU Alpha for non-invasive subcutaneous fat reduction; Ulfit, a medical device used to improve skin elasticity and subcutaneous tissue in the abdomen and thighs; Refit, a medical device that uses RF and negative pressure…
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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.