Kingsmen Resources Ltd (KNG) Fair Value & Analysis
Basic Materials · CA · Market cap A$5.9M
Fair value as of: Jun 26, 2026
Analysis
Kingsmen Resources Ltd (KNG) currently trades at A$0.0450, while our model-based Fair Value estimate is A$0.0293 — implying the stock looks roughly 35.0% overvalued today. We read business quality at 91/100 (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
Kingsmen Resources Ltd., a junior mineral exploration company, engages in the acquisition and exploration of mineral properties in Mexico. It explores for precious metals, silver, gold, lead, zinc, and copper deposits. The company holds a 100% interest in the Las Coloradas Project, which consists of fifteen mining concessions covering an area of approximately 845 hectares located in the Parral Mining District in Chihuahua, Mexico. It also has a 100% interest in the Almoloya project, which consists of five mineral claims covering an area of approximately 866.25 hectares located in the Parral Mining District, Chihuahua, Mexico. The company was formerly known as Tumi Resources Limited and changed its name to Kingsmen Resources Ltd. in July 2015. Kingsmen Resources Ltd. was incorporated in 2000 and is based in Vancouver, Canada.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Kingsmen Resources Ltd (KNG) undervalued?
What is the fair value of KNG?
What is the quality score of KNG?
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.