-
1 Comment
Ambertech Limited is currently in a long term uptrend where the price is trading 19.1% above its 200 day moving average.
From a valuation standpoint, the stock is 99.7% cheaper than other stocks from the Technology sector with a price to sales ratio of 0.2.
Ambertech Limited's total revenue rose by 52.1% to $39M since the same quarter in the previous year.
Its net income has increased by 329.5% to $4M since the same quarter in the previous year.
Finally, its free cash flow grew by 108.9% to $736K since the same quarter in the previous year.
Based on the above factors, Ambertech Limited gets an overall score of 5/5.
ISIN | AU000000AMO9 |
---|---|
Exchange | AU |
CurrencyCode | AUD |
Sector | Technology |
Industry | Electronics & Computer Distribution |
Beta | 0.63 |
---|---|
PE Ratio | None |
Market Cap | 15M |
Target Price | None |
Dividend Yield | None |
Ambertech Limited operates as a technology equipment distribution company in Australia and New Zealand. It operates through Retail, Integrated Solutions, and Professional segments. The Retail segment distributes home entertainment solutions to dealers. The Integrated Solutions segment distributes and supplies custom installation components for home theatre, and commercial installations to dealers and consumers; and distributes projection and display products for business and domestic applications. The Professional segment is involved in the distribution of technology equipment to professional broadcast, film, recording, and sound reinforcement industries. The company was founded in 1987 and is based in Warriewood, Australia.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for AMO.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