-
1 Comment
Orex Minerals Inc is currently in a long term downtrend where the price is trading 18.2% below 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.
Orex Minerals Inc's total revenue sank by nan% to $0 since the same quarter in the previous year.
Its net income has increased by 34.4% to $-424K since the same quarter in the previous year.
Finally, its free cash flow fell by 52.1% to $-640K since the same quarter in the previous year.
Based on the above factors, Orex Minerals Inc gets an overall score of 2/5.
| Industry | Other Industrial Metals & Mining |
|---|---|
| Sector | Basic Materials |
| ISIN | CA68616X1006 |
| CurrencyCode | CAD |
| Exchange | V |
| PE Ratio | None |
|---|---|
| Market Cap | 7M |
| Beta | 0.8 |
| Dividend Yield | 0.0% |
| Target Price | 0.65 |
Orex Minerals Inc., a mineral exploration company, engages in the acquisition and exploration of mineral properties in Mexico and Canada. It owns interests in the Coneto silver-gold project that covers an area of 16,346 hectares of mineral concessions located in the Mesa Central on the eastern flank of the Sierra Madre Occidental Mountains; the Sandra Escobar silver-gold project situated to the north of the town of Tepehuanes, Durango; and the Jumping Josephine gold project totalling 11,200 hectares located in the West Kootenay region of Southeastern British Columbia. The company was incorporated in 1996 and is headquartered in Vancouver, Canada.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for REX.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 2024
