-
1 Comment
Haier Electronics Group Co., Ltd is currently in a long term uptrend where the price is trading 38.6% above its 200 day moving average.
From a valuation standpoint, the stock is 91.2% cheaper than other stocks from the Technology sector with a price to sales ratio of 1.2.
Based on the above factors, Haier Electronics Group Co., Ltd gets an overall score of 2/5.
| Exchange | F |
|---|---|
| CurrencyCode | EUR |
| ISIN | None |
| Sector | Technology |
| Industry | Consumer Electronics |
| Beta | 1.25 |
|---|---|
| Market Cap | 11B |
| PE Ratio | 19.46 |
| Target Price | None |
| Dividend Yield | 1.4% |
Haier Electronics Group Co., Ltd., an investment holding company, engages in the research, development, manufacture, and sale of washing machines and water heaters under the Haier, Casarte, and Leader brands in Mainland China and internationally. It operates through three segments: Washing Machine Business, Water Heater and Water Purifier Business, and Channel Services Business. The Washing Machine Business segment manufactures and sells washing machines. The Water Heater Business segment manufactures and sells water heaters and purifiers. The Channel Services Business segment sells and distributes home appliances and other products, as well as provides after-sale and other value-added consumer services. The company also offers water treatment equipment and home electric appliances, as well as involved in the online sale of home electric appliances. The company was founded in 1984 and is headquartered in Central, Hong Kong.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for HC7B.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
