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Far East Gold Limited (FEG) Fair Value & Analysis

Basic Materials · AU · Market cap A$58.7M

PriceA$0.1500
Fair ValueA$0.0200
Upside-86.7%
Quality87/100
Evidence: Low Range A$0.0200 – A$0.0300

Fair value as of: Jun 26, 2026

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Analysis

Far East Gold Limited (FEG) currently trades at A$0.1500, while our model-based Fair Value estimate is A$0.0200 — implying the stock looks roughly 86.7% overvalued today. We read business quality at 87/100 (high quality), in the Basic Materials 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

Far East Gold Limited, together with its subsidiaries, engages in exploration and evaluation of mineral properties in Australia and Indonesia. It explores for gold and copper deposits. The company was incorporated in 2020 and is based in Brisbane, Australia.

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Frequently asked questions

Is Far East Gold Limited (FEG) undervalued?
As of Jun 26, 2026, our model estimates a fair value of A$0.0200 versus a price of A$0.1500 — about −87% (overvalued). Model-based estimate, not financial advice.
What is the fair value of FEG?
Our 21-model fair value for Far East Gold Limited is A$0.0200 (as of Jun 26, 2026), built from audited fundamentals. The current price is A$0.1500.
What is the quality score of FEG?
Far East Gold Limited has a Quality Score of 87/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.