-
1 Comment
Metcash Limited is currently in a long term uptrend where the price is trading 14.7% above its 200 day moving average.
From a valuation standpoint, the stock is 95.6% cheaper than other stocks from the Consumer Defensive sector with a price to sales ratio of 0.3.
Metcash Limited's total revenue rose by 12.0% to $7B since the same quarter in the previous year.
Its net income has increased by 182.5% to $125M since the same quarter in the previous year.
Finally, its free cash flow grew by 144.0% to $142M since the same quarter in the previous year.
Based on the above factors, Metcash Limited gets an overall score of 5/5.
ISIN | AU000000MTS0 |
---|---|
Sector | Consumer Defensive |
Industry | Food Distribution |
Exchange | AU |
CurrencyCode | AUD |
Market Cap | 3B |
---|---|
PE Ratio | 13.19 |
Target Price | 3.7862 |
Beta | 0.26 |
Dividend Yield | 5.4% |
Metcash Limited operates as a wholesale distribution and marketing company in Australia. It operates through Food, Liquor, and Hardware segments. The Food segment distributes a range of products and services to independent supermarket and convenience retail outlets. The Liquor segment engages in the distribution of liquor products to independent retail outlets and hotels. The Hardware segment distributes hardware products to independent retail outlets; and operates company owned retail stores. It sells its products under the IGA, Foodland, Mitre 10, Home Hardware, Total Tools, Cellarbrations, IGA Liquor, and the Bottle-O brand names. Metcash Limited was founded in 1927 and is based in Macquarie Park, Australia.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for MTS.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