Janison Education Group (JAN) Fair Value & Analysis
Technology · AU · Market cap A$26.2M
Fair value as of: Jun 26, 2026
Analysis
Janison Education Group (JAN) currently trades at A$0.0990, while our model-based Fair Value estimate is A$0.4564 — implying the stock looks roughly 361.0% undervalued today. We read business quality at 95/100 (high quality), in the Technology 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
Janison Education Group Limited provides online assessment software, assessment products, and assessment services in Australia, New Zealand, Asia, and internationally. It operates through Product and Platform segments. The company offers exam products, exam items, and associated exam services to schools, parents, and teachers. It also provides exam enterprise-grade assessment platform technology and event management services for organizations, national education authorities, and accreditation bodies. In addition, the company offers assessment services, such as in-person exam invigilation, customer support, custom software development, marking, and test development; and learning management software tool for large corporates. It serves state and federal education bodies, schools, and parents. The company was formerly known as HJB Corporation Ltd. and changed its name to Janison Education Group Limited in December 2017. Janison Education Group Limited was founded in 1998 and is headqua…
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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.