-
1 Comment
Golden Energy and Resources Limited is currently in a long term uptrend where the price is trading 99.9% above its 200 day moving average.
From a valuation standpoint, the stock is 99.5% cheaper than other stocks from the Energy sector with a price to sales ratio of 0.2.
Golden Energy and Resources Limited's total revenue rose by 226.9% to $1B since the same quarter in the previous year.
Its net income has increased by 220.8% to $8M since the same quarter in the previous year.
Finally, its free cash flow grew by 213.0% to $28M since the same quarter in the previous year.
Based on the above factors, Golden Energy and Resources Limited gets an overall score of 5/5.
| Sector | Energy |
|---|---|
| ISIN | SG1AI1000008 |
| Exchange | SG |
| CurrencyCode | SGD |
| Industry | Thermal Coal |
| Dividend Yield | 0.0% |
|---|---|
| Beta | 0.13 |
| PE Ratio | 2.76 |
| Target Price | 1.27 |
| Market Cap | 3B |
Golden Energy and Resources Limited, an investment holding company, engages in the provision of management services, coal mining and trading, and forestry activities. The company operates through Energy Coal, Metallurgical Coal, and Non-Coal Business segments. It involves in exploration, mining, processing, and marketing of energy and metallurgical coal, as well as gold mining services. Golden Energy and Resources Limited operates in China, Indonesia, India, Japan, South Korea, Brazil, Spain, Germany, Thailand, Australia, Finland, the Philippines, the Netherlands, Malaysia, and internationally. The company is based in Singapore. Golden Energy and Resources Limited is a subsidiary of PT Dian Swastatika Sentosa Tbk.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for AUE.SG 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
