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NICO Resources Limited (NC1) Fair Value & Analysis

Basic Materials · AU · Market cap A$23.3M

PriceA$0.1250
Fair ValueA$0.0300
Upside-76.0%
Quality95/100
Evidence: Low Range A$0.0200 – A$0.0300

Fair value as of: Jun 26, 2026

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Analysis

NICO Resources Limited (NC1) currently trades at A$0.1250, while our model-based Fair Value estimate is A$0.0300 — implying the stock looks roughly 76.0% overvalued today. We read business quality at 95/100 (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

NICO Resources Limited engages in the acquisition, exploration, and development of mineral properties in Australia. Its flagship project is the Wingellina nickel-cobalt project located in Western Australia. The company was incorporated in 2021 and is based in Perth, Australia.

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Frequently asked questions

Is NICO Resources Limited (NC1) undervalued?
As of Jun 26, 2026, our model estimates a fair value of A$0.0300 versus a price of A$0.1250 — about −76% (overvalued). Model-based estimate, not financial advice.
What is the fair value of NC1?
Our 21-model fair value for NICO Resources Limited is A$0.0300 (as of Jun 26, 2026), built from audited fundamentals. The current price is A$0.1250.
What is the quality score of NC1?
NICO Resources Limited has a Quality Score of 95/100, 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.