Bioalpha Holdings (0179) Fair Value & Analysis
Consumer Defensive · MY · Market cap 21.3M MYR
Fair value as of: Jun 26, 2026
Analysis
Bioalpha Holdings (0179) currently trades at 0.0150 MYR, while our model-based Fair Value estimate is 0.0143 MYR — implying the stock looks roughly 5.0% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Defensive 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
Bioalpha Holdings Berhad, an investment holding company, engages in the manufacture and sale of health supplement products in Malaysia, China, and internationally. The company operates through two segments, Trading and Manufacturing. The company also engages in the provision of advertising and promotion services for health supplements, nutrition products, personal care, functional food, and healthcare products; import, export, cultivation, manufacture, distribution, and trade of various agro products and medical herbs; and planting, growing, and trade of herbs, fruits, agricultural, and agro and organic products. In addition, the company is involved in the wholesale and retail trade of pharmaceutical and traditional medicines, healthcare, nutritional products, and food and beverages; procurement and sale of agricultural products; land development services; import and export of medicines and edible bacteria; sale of food through the internet; and management and consulting activities.…
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Frequently asked questions
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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.