-
1 Comment
Impulse (Qingdao) Health Tech Co.,Ltd is currently in a long term downtrend where the price is trading 3.1% below its 200 day moving average.
From a valuation standpoint, the stock is 68.9% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.6.
Impulse (Qingdao) Health Tech Co.,Ltd's total revenue sank by 8.3% to $218M since the same quarter in the previous year.
Its net income has dropped by 55.8% to $12M since the same quarter in the previous year.
Finally, its free cash flow grew by 31.9% to $-8M since the same quarter in the previous year.
Based on the above factors, Impulse (Qingdao) Health Tech Co.,Ltd gets an overall score of 2/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE1000032T3 |
| Sector | Consumer Cyclical |
| Industry | Leisure |
| Target Price | None |
|---|---|
| Dividend Yield | 0.4% |
| Market Cap | 3B |
| PE Ratio | 26.42 |
| Beta | 0.57 |
Impulse (Qingdao) Health Tech Co.,Ltd. engages in research, development, manufacture, and sale of fitness equipment in China and internationally. It offers stair climbers; treadmills; upright, spinning, and recumbent bikes; elliptical and indoor cycles; and strength, group training, and outdoor fitness equipment, as well as ultra bike and rower. The company also provides after-sales services. It serves gymnasiums, governments, enterprises and institutions, military and police units, colleges and universities and other commercial customers and home users. Impulse (Qingdao) Health Tech Co.,Ltd. was founded in 2004 and is headquartered in Qingdao, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002899.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
