Helixmith Co (084990) Fair Value & Analysis
Consumer Non-Cyclicals · KR · Market cap 226B KRW
Fair value as of: Jun 25, 2026
Analysis
Helixmith Co (084990) currently trades at 4,255 KRW, while our model-based Fair Value estimate is 723.03 KRW — implying the stock looks roughly 83.0% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Non-Cyclicals 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
Helixmith Co., Ltd, a biotechnology company, discovers and develops biopharmaceuticals for human diseases. The company has a pipeline of novel biologics and herbal therapeutics in the areas of cardiovascular disease, cancer, and immune disorder, with clinical studies ongoing in the United States, Korea, and China. Its flagship product is VM202, a DNA-based drug for cardiovascular and neurological diseases. The company's pipeline products include VM206, a therapeutic cancer vaccine targeting HER2/neu positive breast or ovarian cancer; and VM501, a re-engineered form of interleukin 11 targeting chemotherapy-induced thrombocytopenia. Its clinical trials biologics comprise VM202-DPN, VM202-PAD, VM501, VM202-ALS, VM202-CAD, and VM206. The company was formerly known as ViroMed Co., Ltd. and changed its name to Helixmith Co., Ltd in April 2019. Helixmith Co., Ltd was incorporated in 1996 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.