-
1 Comment
Hawthorn Resources Limited is currently in a long term downtrend where the price is trading 43.2% below its 200 day moving average.
From a valuation standpoint, the stock is 99.9% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 0.6.
Hawthorn Resources Limited's total revenue sank by 99.8% to $80K since the same quarter in the previous year.
Its net income has dropped by 118.3% to $-2M since the same quarter in the previous year.
Finally, its free cash flow fell by 113.2% to $-1M since the same quarter in the previous year.
Based on the above factors, Hawthorn Resources Limited gets an overall score of 1/5.
| Exchange | AU |
|---|---|
| CurrencyCode | AUD |
| Industry | Gold |
| ISIN | AU000000HAW2 |
| Sector | Basic Materials |
| Market Cap | 34M |
|---|---|
| PE Ratio | 604.17 |
| Target Price | None |
| Beta | -0.39 |
| Dividend Yield | None |
Hawthorn Resources Limited engages in the exploration and development of mineral resources in Australia. The company explores for iron ore, gold, magnetite, lithium, nickel, copper, and other base metals. It holds a 70% interest in the Trouser Legs Mining Joint Venture Project, and a 37% interest in the Mt Bevan critical minerals project and 28% interest in the Mt Bevan magnetite project located in Central Yilgarn, Western Australia. The company also holds a 34% stake in a joint venture for the exploration and extraction of other critical minerals, including lithium, alongside Legacy Iron Ore Limited and Hancock Magnetite Holdings Pty Ltd. Hawthorn Resources Limited was incorporated in 1985 and is based in Melbourne, Australia.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for HAW.AU 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
