Great Northern Minerals Limited (GNM) Fair Value & Analysis
Basic Materials · AU · Market cap A$19.2M
Fair value as of: Jun 26, 2026
Analysis
Great Northern Minerals Limited (GNM) currently trades at A$0.0300, while our model-based Fair Value estimate is A$0.0300 — implying the stock looks roughly 0.0% undervalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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
Great Northern Minerals Limited engages in the exploration and development of mineral properties in Australia and Finland. It explores for lithium, gold, and copper deposits. The company holds interests in the Finland lithium properties comprising the Sukula project that covers approximately 174.3 square kilometers and the Kuusisuo project that consists of approximately 362 square kilometers. It also holds interests in the Douglas Creek project situated in north Queensland Australia. The company was formerly known as Greenpower Energy Limited and changed its name to Great Northern Minerals Limited in October 2019. Great Northern Minerals Limited was incorporated in 1899 and is based in Perth, Australia.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Great Northern Minerals Limited (GNM) undervalued?
What is the fair value of GNM?
What is the quality score of GNM?
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.