-
1 Comment
Longxing Chemical Stock Co., Ltd is currently in a long term uptrend where the price is trading 53.0% above its 200 day moving average.
From a valuation standpoint, the stock is 75.1% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 1.0.
Longxing Chemical Stock Co., Ltd's total revenue sank by 16.2% to $614M since the same quarter in the previous year.
Its net income has increased by 22.4% to $19M since the same quarter in the previous year.
Finally, its free cash flow fell by 118.0% to $-22M since the same quarter in the previous year.
Based on the above factors, Longxing Chemical Stock Co., Ltd gets an overall score of 3/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE100000R00 |
| Sector | Basic Materials |
| Industry | Specialty Chemicals |
| Target Price | 9.39 |
|---|---|
| Beta | 0.48 |
| PE Ratio | 123.25 |
| Market Cap | 2B |
| Dividend Yield | None |
Longxing Technology Group Co., Ltd. engages in the research and development, production, and sale of carbon-based and silicon-based nanomaterials in China and internationally. It offers rubber carbon blacks, such as standard grades and semi-reinforcing, as well as customized products with low polycyclic aromatic hydrocarbons and high purity; plastics and MB grade products; and nano-grade carbon black, silica, and electrolytic carbon. The company was formerly known as Longxing Chemical Stock Co., Ltd. and changed its name to Longxing Technology Group Co., Ltd. in January 2025. Longxing Technology Group Co., Ltd. was founded in 1994 and is headquartered in Shahe, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002442.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 2026