-
1 Comment
Wolong Electric Drive Group Co., Ltd is currently in a long term uptrend where the price is trading 1.8% above its 200 day moving average.
From a valuation standpoint, the stock is 76.3% cheaper than other stocks from the Industrials sector with a price to sales ratio of 1.2.
Wolong Electric Drive Group Co., Ltd's total revenue rose by 1.7% to $3B since the same quarter in the previous year.
Its net income has increased by 29.9% to $261M since the same quarter in the previous year.
Finally, its free cash flow fell by 60.3% to $124M since the same quarter in the previous year.
Based on the above factors, Wolong Electric Drive Group Co., Ltd gets an overall score of 4/5.
| Exchange | SHG |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE000001BJ3 |
| Sector | Industrials |
| Industry | Electrical Equipment & Parts |
| Beta | 0.95 |
|---|---|
| Market Cap | 69B |
| PE Ratio | 70.0 |
| Target Price | 15.5 |
| Dividend Yield | 0.3% |
Wolong Electric Group Co.,Ltd. manufactures and sells motors and controls in China. The company offers low voltage motors, high voltage motors, generators, drives and control, home appliance motors, EC motors and fans, and transformers; system solutions, such as energy saving retrofit, coal industry system, and steam to electric system solutions; automation solutions; and digital and full life services. It serves various industries, including smart building, green industry, and E-mobility. The company was formerly known as Wolong Electric Group Co., Ltd. Wolong Electric Group Co.,Ltd. was founded in 1984 and is based in Shaoxing, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 600580.SHG 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
