-
1 Comment
Zhejiang Kaier New Materials Co.,Ltd is currently in a long term uptrend where the price is trading 29.2% above its 200 day moving average.
From a valuation standpoint, the stock is 94.3% more expensive than other stocks from the Basic Materials sector with a price to sales ratio of 7.8.
Zhejiang Kaier New Materials Co.,Ltd's total revenue sank by 32.5% to $114M since the same quarter in the previous year.
Its net income has dropped by 94.6% to $1M since the same quarter in the previous year.
Finally, its free cash flow grew by 94.0% to $-2M since the same quarter in the previous year.
Based on the above factors, Zhejiang Kaier New Materials Co.,Ltd gets an overall score of 2/5.
| Sector | Basic Materials |
|---|---|
| Industry | Steel |
| Exchange | SHE |
| CurrencyCode | CNY |
| ISIN | CNE1000014Z8 |
| Beta | 0.58 |
|---|---|
| Market Cap | 2B |
| PE Ratio | 89.6 |
| Target Price | None |
| Dividend Yield | 2.3% |
Zhejiang Kaier New Materials Co.,Ltd. engages in the design, research, development, manufacture, promotion, and sale of functional enamel materials in China. The company offers interior facade decorative enamel materials, enamel panels, green building curtain wall materials, and industrial protective enamel materials. Its products are mainly used in the construction of public facilities, such as subways and tunnels, thermal power and non-electric energy-saving and environmental protection facilities construction, property building construction and other industries. Zhejiang Kaier New Materials Co.,Ltd. was founded in 2003 and is based in Jinhua, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 300234.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
