-
1 Comment
Fancamp Exploration Ltd is currently in a long term uptrend where the price is trading 4.9% above its 200 day moving average.
From a valuation standpoint, the stock is 100.0% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 0.0.
Fancamp Exploration Ltd's total revenue sank by nan% to $0 since the same quarter in the previous year.
Its net income has increased by 258.0% to $3M since the same quarter in the previous year.
Finally, its free cash flow grew by 50.4% to $-440K since the same quarter in the previous year.
Based on the above factors, Fancamp Exploration Ltd gets an overall score of 4/5.
| Sector | Basic Materials |
|---|---|
| Industry | Other Industrial Metals & Mining |
| Exchange | V |
| CurrencyCode | CAD |
| ISIN | CA30710P1027 |
| Market Cap | 17M |
|---|---|
| PE Ratio | 2.33 |
| Target Price | None |
| Beta | 1.75 |
| Dividend Yield | None |
Fancamp Exploration Ltd. engages in the exploration and development of mineral properties. It explores for copper, gold, zinc, titanium, chromium, and rare earth, as well as iron ore deposits. The company owns various mineral resource properties, including the Riley Brook, Abitibi Corporation, Beauce Main BVB, Beauce Timrod, Clinton, DiLeo Lake, Grasset Laforest, Robidoux, Grevet, Harvey Hill, Kinross, Lac Baude Baril, Magpie, Mingan, Risborough, Stoke, Optionor, and Desolation Lake, as well as option to own interests in Dorothy, Mallard Heenan, and Koper Lake-McFaulds properties. Fancamp Exploration Ltd. was incorporated in 1986 and is headquartered in Burnaby, Canada.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for FNC.V using our backtest tool. PyInvesting provides the backtesting software for you to backtest your investment strategy. Our backtest software is written using Python code and allows you to backtest stock, backtest etf, backtest options, backtest crypto and backtest forex online. Our backtesting Python framework is highly robust and gives you a realistic simulation of how your strategy would have performed in the past using backtest data.
© PyInvesting 2025
