-
1 Comment
Zhe Jiang Hai Liang Co., Ltd is currently in a long term uptrend where the price is trading 15.7% above its 200 day moving average.
From a valuation standpoint, the stock is 90.0% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 0.4.
Zhe Jiang Hai Liang Co., Ltd's total revenue sank by 0.6% to $11B since the same quarter in the previous year.
Its net income has increased by 1.8% to $179M since the same quarter in the previous year.
Finally, its free cash flow fell by 171.9% to $-950M since the same quarter in the previous year.
Based on the above factors, Zhe Jiang Hai Liang Co., Ltd gets an overall score of 3/5.
| Sector | Basic Materials |
|---|---|
| Industry | Copper |
| Exchange | SHE |
| CurrencyCode | CNY |
| ISIN | CNE1000008X5 |
| PE Ratio | 18.58 |
|---|---|
| Dividend Yield | 1.9% |
| Target Price | 13 |
| Market Cap | 18B |
| Beta | 0.28 |
Zhe Jiang Hai Liang Co., Ltd engages in the production, sale, and service of copper products, materials of conductors, and aluminum-based materials. Its products include copper coil tubes, straight tubes, fittings, copper and brass bars, copper bus bars, aluminum tubes, denitration catalysts, and other equipment. The company's products are used in household appliance, equipment and instrument, ship, electricity, new energy vehicles, energy storage, photovoltaic, wind energy, semiconductor, 5G communication, and others. Zhe Jiang Hai Liang Co., Ltd was founded in 2001 and is based in Zhuji, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002203.SHE 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
