-
1 Comment
Yeebo (International Holdings) Limited is currently in a long term uptrend where the price is trading 55.0% above its 200 day moving average.
From a valuation standpoint, the stock is 83.2% cheaper than other stocks from the Technology sector with a price to sales ratio of 2.3.
Yeebo (International Holdings) Limited's total revenue sank by 0.0% to $225M since the same quarter in the previous year.
Its net income has dropped by 0.0% to $32M since the same quarter in the previous year.
Finally, its free cash flow grew by 1.2% to $24M since the same quarter in the previous year.
Based on the above factors, Yeebo (International Holdings) Limited gets an overall score of 3/5.
| Exchange | F |
|---|---|
| CurrencyCode | EUR |
| ISIN | None |
| Sector | |
| Industry |
| Market Cap | 283M |
|---|---|
| PE Ratio | 13.05 |
| Target Price | None |
| Beta | 0.31 |
| Dividend Yield | 7.3% |
Yeebo (International Holdings) Limited, an investment holding company, manufactures, trades in, and sells liquid crystal display (LCD) and LCD modules. It also offers thin film transistor modules and capacitive touch panel products. The company serves customers in electronic market sectors, including industrial applications, telecommunications, medical equipment, and electronic consumable products. It operates in Hong Kong, Mainland China, Japan, Taiwan, other Asian countries, the United States, Germany, Spain, other European countries, and internationally. The company was founded in 1988 and is headquartered in Kwai Chung, Hong Kong. Yeebo (International Holdings) Limited is a subsidiary of Antrix Investment Limited.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for YIH.F 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
