Applied BioCode Corporation (6598) Fair Value & Analysis
Healthcare · TW · Market cap 2.5B TWD
Fair value as of: Jun 24, 2026
Analysis
Applied BioCode Corporation (6598) currently trades at 23.20 TWD, while our model-based Fair Value estimate is 28.15 TWD — implying the stock looks roughly 21.3% undervalued today. We read business quality at 95/100 (high quality), in the Healthcare sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
Applied BioCode Corporation designs, develops, and commercializes multiplex diagnostic testing products in California. Its products include the BioCode MDx 3000 system, an automated molecular diagnostic system that automates the detection steps, PCR amplification, and hybridization and target capture; and the BioCode 2500 analyzer, a system that reads each barcode and quantifies the BMB target using the fluorescence signal intensity. The company develops assays, such as BioCode SARS-CoV-2 Assay, an assay for the detection of SARS-CoV-2 nucleic acid in nasopharyngeal swabs; and CoV-2 Flu Assay for detection of RNA and various Influenza, as well as offers gastrointestinal and respiratory pathogen panel related products. In addition, it provides BioCode Fungal Panel, a multiplexed deoxyribonucleic acid (DNA) amplification test; and BioCode STI + Resistance Panel (RUO), a multiplex nucleic acid amplification test. Further, the company offers barcoded magnetic bead accessories. Applied B…
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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.