-
1 Comment
Jiangxi Special Electric Motor Co.,Ltd is currently in a long term uptrend where the price is trading 94.3% above its 200 day moving average.
From a valuation standpoint, the stock is 8.7% more expensive than other stocks from the Industrials sector with a price to sales ratio of 5.5.
Jiangxi Special Electric Motor Co.,Ltd's total revenue sank by 11.6% to $441M since the same quarter in the previous year.
Its net income has increased by 99.7% to $-7M since the same quarter in the previous year.
Finally, its free cash flow grew by 223.3% to $247M since the same quarter in the previous year.
Based on the above factors, Jiangxi Special Electric Motor Co.,Ltd gets an overall score of 3/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE1000007F4 |
| Sector | Industrials |
| Industry | Electrical Equipment & Parts |
| Beta | 0.55 |
|---|---|
| PE Ratio | None |
| Target Price | 18.34 |
| Market Cap | 12B |
| Dividend Yield | None |
Jiangxi Special Electric Motor Co.,Ltd researches, develops, produces, and sells motor and lithium products in China. The company offers construction machinery, hoisting metallurgical, wind power supporting, servo, military, and energy vehicle motors. Its products are used in construction tower cranes, lifting metallurgical machinery, wind power equipment, elevators and escalators, textile machines, embroidery machines, packaging machines, printing machines, CNC machine tools, robots, ships, armored vehicles, heavy trucks, sanitation vehicles, and other fields. Jiangxi Special Electric Motor Co.,Ltd is based in Yichun, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002176.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
