Cogstate Limited (CGS) Fair Value & Analysis
Healthcare · AU · Market cap A$426M
Fair value as of: Jun 24, 2026
Analysis
Cogstate Limited (CGS) currently trades at A$2.76, while our model-based Fair Value estimate is A$0.8600 — implying the stock looks roughly 68.8% 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
Cogstate Limited, a neuroscience solutions company, engages in the creation, validation, and commercialization of digital brain health assessments worldwide. It offers digital cognitive assessment, endpoint data quality (rater services), remote assessment, scientific consulting, healthcare cognitive screening, and research and academic collaboration solutions for various therapeutic areas, including Alzheimer's disease and dementia, preclinical Alzheimer's disease, pediatrics and rare disease, Parkinson's disease, multiple sclerosis, schizophrenia, oncology, safety, and sleep and mood disorders. The company also designs and provides quality assurance services in clinical trials focused on the administration, scoring, and recording of conventional brain health assessments. In addition, it develops a tool for primary care physicians and/or hospitals to assess cognitive decline. Its technology and associated services are used to quantify the effect of disease and drugs, devices, or oth…
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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.