-
1 Comment
CI Resources Limited is currently in a long term uptrend where the price is trading 24.0% above 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 0.7.
CI Resources Limited's total revenue rose by 11.1% to $76M since the same quarter in the previous year.
Its net income has increased by 138.7% to $6M since the same quarter in the previous year.
Finally, its free cash flow grew by 73.2% to $-2M since the same quarter in the previous year.
Based on the above factors, CI Resources Limited gets an overall score of 5/5.
| Exchange | AU |
|---|---|
| CurrencyCode | AUD |
| ISIN | AU000000CII5 |
| Sector | Industrials |
| Industry | Integrated Freight & Logistics |
| Market Cap | 149M |
|---|---|
| PE Ratio | 5.84 |
| Dividend Yield | 7.8% |
| Target Price | None |
| Beta | 0.4 |
CI Resources Limited, together with its subsidiaries, engages in mining, processing, and sale of phosphate rock, phosphate dust, and chalk in Australia, Asia, North America, Europe, Africa, and Oceania. It operates through Fertiliser, Farming, and Logistics segments. The company also provides earthmoving, fuel pilotage, and maintenance services to other organizations in Christmas Island; operates a palm oil estate; and cultivates, processes, and sells palm oil products. In addition, it offers shipping, stevedoring, investment, and marketing services, as well as involved in the trading, importing, and exporting of commodities. The company was incorporated in 1987 and is based in Burswood, Australia.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for CII.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
