Locksley Resources Limited (LKYRF) Fair Value & Analysis
Basic Materials · US · Market cap $20.4M
Fair value as of: Jun 26, 2026
Analysis
Locksley Resources Limited (LKYRF) currently trades at $0.0470, while our model-based Fair Value estimate is $0.0296 — implying the stock looks roughly 37.0% overvalued today. We read business quality at 78/100 (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
Locksley Resources Limited engages in the acquisition, exploration, and development of mineral resources projects in Australia and the United States. The company primarily explores for copper, antimony, and gold deposits, as well as rare earth elements. It holds interests in the Tottenham project, which comprises four granted exploration licenses covering an area of approximately 470 square kilometers located in the Cobar-Girilambone District in Central New South Wales; and the Mojave project that includes 297 claims covering an area of approximately 20 square kilometers located in California. It also holds 100% interest in the Iron Duke Copper Gold Project located in New South Wales, Australia. The company has a strategic collaboration with Columbia University to develop methods for recovering and processing rare earth elements and critical metals for its Mojave Project. The company was incorporated in 2018 and is based in Northbridge, Australia.
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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.