-
1 Comment
Jatcorp Limited is currently in a long term downtrend where the price is trading 8.1% below its 200 day moving average.
From a valuation standpoint, the stock is 91.2% cheaper than other stocks from the Consumer Defensive sector with a price to sales ratio of 0.6.
Jatcorp Limited's total revenue sank by 54.0% to $14M since the same quarter in the previous year.
Its net income has dropped by 24.6% to $-3M since the same quarter in the previous year.
Finally, its free cash flow grew by 86.6% to $-65K since the same quarter in the previous year.
Based on the above factors, Jatcorp Limited gets an overall score of 2/5.
Exchange | AU |
---|---|
CurrencyCode | AUD |
Sector | Consumer Defensive |
Industry | Packaged Foods |
ISIN | AU000000JAT4 |
Market Cap | 18M |
---|---|
Target Price | None |
PE Ratio | None |
Beta | 0.83 |
Dividend Yield | None |
Jatcorp Limited engages in the production and sale of dairy and plant-based health products and supplements products in Australia, China, and New Zealand. It provides cow and goat milk powder-based products; and cream and skim milk powders. The company provides its products under the Jinvigorate, Neurio, iOne, and Moroka brand names. In addition, it operates as a trade specialist for fast-moving consumer goods. The company sells its products through retail and e-commerce platforms. The company was formerly known as Jatenergy Limited and changed its name to Jatcorp Limited in June 2020. Jatcorp Limited was incorporated in 2006 and is headquartered in Derrimut, Australia.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for JAT.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