AJ Lucas Group (AJLGF) Fair Value & Analysis
Basic Materials · US · Market cap $12.1M
Fair value as of: Jun 26, 2026
Analysis
AJ Lucas Group (AJLGF) currently trades at $0.0088, while our model-based Fair Value estimate is $0.0089 — implying the stock looks roughly 1.2% 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: high) — always confirm before acting.
About the company
AJ Lucas Group Limited, together with its subsidiaries, provides drilling services in Australia. The company operates in two segments, Drilling and Oil and Gas Operations. The Drilling segment provides integrated professional drilling services primarily for exploration and degasification of coal mines, including recovery and commercialization of coal seam gas and associated services. The Oil and Gas Operations segment engages in the exploration and development of unconventional and conventional hydrocarbons in the United Kingdom. The company also offers engineering services, such as design of wells, drilling optimisation, and professional steering services, as well as specialised equipment for directional drilling programmes. It serves the energy, mining, and infrastructure sectors. The company was incorporated in 1993 and is headquartered in Brisbane, Australia. AJ Lucas Group Limited is a subsidiary of Kerogen Investments No. 1 (HK) Limited.
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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.