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Koryx Copper S.A (KRYXF) Fair Value & Analysis

Basic Materials · US · Market cap $313M

Price$2.24
Fair Value$0.5400
Upside-75.9%
Quality95/100
Evidence: Low Range $0.4100 – $0.6800

Fair value as of: Jun 24, 2026

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Analysis

Koryx Copper S.A (KRYXF) currently trades at $2.24, while our model-based Fair Value estimate is $0.5400 — implying the stock looks roughly 75.9% 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

Koryx Copper S.A. operates as a copper exploration and development company. It focuses on advancing its 100% owned Haib Copper Project in Namibia, as well as building a portfolio of copper exploration licenses in Zambia. Its Haib Copper Project is a copper/molybdenum/gold porphyry deposit in southern Namibia. The company is headquartered in Vancouver, Canada.

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Frequently asked questions

Is Koryx Copper S.A (KRYXF) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $0.5400 versus a price of $2.24 — about −76% (overvalued). Model-based estimate, not financial advice.
What is the fair value of KRYXF?
Our 21-model fair value for Koryx Copper S.A is $0.5400 (as of Jun 24, 2026), built from audited fundamentals. The current price is $2.24.
What is the quality score of KRYXF?
Koryx Copper S.A 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.