-
1 Comment
Shandong Longertek Technology Co., Ltd is currently in a long term downtrend where the price is trading 16.1% below its 200 day moving average.
From a valuation standpoint, the stock is 28.1% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 3.7.
Shandong Longertek Technology Co., Ltd's total revenue rose by 38.2% to $142M since the same quarter in the previous year.
Its net income has increased by 65.7% to $18M since the same quarter in the previous year.
Finally, its free cash flow fell by 39.7% to $-54M since the same quarter in the previous year.
Based on the above factors, Shandong Longertek Technology Co., Ltd gets an overall score of 3/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| Sector | Consumer Cyclical |
| Industry | Auto Parts |
| ISIN | CNE100003QD9 |
| PE Ratio | None |
|---|---|
| Target Price | None |
| Dividend Yield | 0.6% |
| Market Cap | 1B |
| Beta | 0.39 |
Shandong Longertek Technology Co., Ltd. engages in the research, development, production, sale, and maintenance of rail transit vehicle air conditioners and their control systems in China and internationally. It offers track and new energy vehicle air conditioners, thermal management products, air energy heat pump drying equipment, digital energy intelligent environmental control products, and their control systems, as well as new energy equipment, professional computer room temperature control products, and industrial integrated air conditioners. The company was founded in 2000 and is based in Jinan, the People's Republic of China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 300594.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
