-
1 Comment
Zhejiang Changsheng Sliding Bearings Co., Ltd is currently in a long term uptrend where the price is trading 24.3% above its 200 day moving average.
From a valuation standpoint, the stock is 22.5% more expensive than other stocks from the Industrials sector with a price to sales ratio of 6.2.
Zhejiang Changsheng Sliding Bearings Co., Ltd's total revenue rose by 7.4% to $165M since the same quarter in the previous year.
Its net income has increased by 9.0% to $43M since the same quarter in the previous year.
Finally, its free cash flow grew by 120.4% to $41M since the same quarter in the previous year.
Based on the above factors, Zhejiang Changsheng Sliding Bearings Co., Ltd gets an overall score of 4/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| Sector | Industrials |
| Industry | Specialty Industrial Machinery |
| ISIN | CNE1000035C2 |
| Target Price | 21.05 |
|---|---|
| Beta | -0.2 |
| Dividend Yield | 0.5% |
| PE Ratio | 99.77 |
| Market Cap | 25B |
Zhejiang Changsheng Sliding Bearings Co., Ltd. researches, develops, produces, and sells lubricated bearings and polymers in China and internationally. It offers self-lubricating bearings, low-friction parts, and related precision castings. Its products are used in automobiles, engineering machinery, robots, energy (traditional and renewable), port machinery, plastic machinery, agricultural machinery and other industries. Zhejiang Changsheng Sliding Bearings Co., Ltd. was founded in 1995 and is headquartered in Jiashan, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 300718.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
