-
1 Comment
K & P International Holdings Limited is currently in a long term uptrend where the price is trading 7.7% above its 200 day moving average.
From a valuation standpoint, the stock is 79.8% cheaper than other stocks from the Technology sector with a price to sales ratio of 0.7.
K & P International Holdings Limited's total revenue rose by 24.4% to $200M since the same quarter in the previous year.
Its net income has increased by 276.5% to $53M since the same quarter in the previous year.
Finally, its free cash flow fell by 0.0% to $7M since the same quarter in the previous year.
Based on the above factors, K & P International Holdings Limited gets an overall score of 4/5.
| Exchange | HK |
|---|---|
| CurrencyCode | HKD |
| ISIN | BMG5313X1011 |
| Industry | Electronic Components |
| Sector | Technology |
| PE Ratio | None |
|---|---|
| Dividend Yield | 10.% |
| Beta | 0.57 |
| Market Cap | 96M |
| Target Price | None |
K & P International Holdings Limited, an investment holding company, engages in the manufacture and sale of precision parts and components in Hong Kong, Mainland China, Japan and other Asian countries, North America, South America, Europe, and internationally. The company offers precision parts and components, such as keypads and liquid crystal displays, as well as synthetic rubber, and plastic components and parts; and management and administrative services. It is also involved in the design, manufacture, and sale of consumer electronics products, including time, weather forecasting, and other products. The company was founded in 1985 and is headquartered in Kwai Chung, Hong Kong.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 0675.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 2026
