-
1 Comment
Torex Gold Resources Inc is currently in a long term downtrend where the price is trading 17.1% below its 200 day moving average.
From a valuation standpoint, the stock is 99.7% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 1.5.
Torex Gold Resources Inc's total revenue rose by 32.4% to $252M since the same quarter in the previous year.
Its net income has increased by 161.8% to $92M since the same quarter in the previous year.
Finally, its free cash flow grew by 12.1% to $88M since the same quarter in the previous year.
Based on the above factors, Torex Gold Resources Inc gets an overall score of 4/5.
| CurrencyCode | CAD |
|---|---|
| Industry | Gold |
| Exchange | TO |
| ISIN | CA8910546032 |
| Sector | Basic Materials |
| Market Cap | 4B |
|---|---|
| Beta | 1.28 |
| PE Ratio | 21.11 |
| Target Price | 51.8182 |
| Dividend Yield | None |
Torex Gold Resources Inc. operates as an intermediate gold producer. The company engages in the exploration, development, and operation of principal asset comprising 100% owned the Morelos Gold property, including Morelos Complex, which includes the El Limón Guajes Mine Complex; the Media Luna project, the EPO project, a processing plant, and related infrastructure that covers an area of approximately 29,000 hectares located southwest of Mexico City. It also mines for silver, copper, and carbon deposits. The company was formerly known as Gleichen Resources Ltd. and changed its name to Torex Gold Resources Inc. in April 2010. Torex Gold Resources Inc. was incorporated in 1980 and is based in Toronto, Canada.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for TXG.TO 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
