-
1 Comment
Artini Holdings Limited is currently in a long term downtrend where the price is trading 24.9% below its 200 day moving average.
From a valuation standpoint, the stock is 75.2% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.2.
Artini Holdings Limited's total revenue sank by 16.1% to $57M since the same quarter in the previous year.
Its net income has dropped by 64.6% to $3M since the same quarter in the previous year.
Finally, its free cash flow fell by 169.8% to $-9M since the same quarter in the previous year.
Based on the above factors, Artini Holdings Limited gets an overall score of 1/5.
| Sector | Consumer Cyclical |
|---|---|
| ISIN | BMG051121264 |
| Industry | Luxury Goods |
| Exchange | HK |
| CurrencyCode | HKD |
| Market Cap | 523M |
|---|---|
| PE Ratio | 39.5 |
| Target Price | None |
| Beta | -0.18 |
| Dividend Yield | None |
Artini Holdings Limited, an investment holding company, sells fashion accessories products in Hong Kong, Macao, and the People Republic of China. It operates through Integrated Fashion Accessories Platform Business; and Skincare and Health Product Sales Platform Business segments. The company offers its products, such as necklaces, bracelets, earrings, and brooches under the brand name Artini. It also operates Magic B2B, a cross-border e-commerce platform that focuses on spot wholesale, OEM and ODM, original brand direct sales, and hot-selling promotions. In addition, it sells skincare and health products through online platform. Artini Holdings Limited was founded in 1992 and is based in Kowloon, Hong Kong.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 0789.HK 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
