-
1 Comment
Qingdao Topscomm Communication INC is currently in a long term downtrend where the price is trading 13.4% below its 200 day moving average.
From a valuation standpoint, the stock is 58.9% cheaper than other stocks from the Technology sector with a price to sales ratio of 3.3.
Qingdao Topscomm Communication INC's total revenue rose by 30.5% to $547M since the same quarter in the previous year.
Its net income has dropped by 7.4% to $70M since the same quarter in the previous year.
Finally, its free cash flow grew by 104.4% to $5M since the same quarter in the previous year.
Based on the above factors, Qingdao Topscomm Communication INC gets an overall score of 3/5.
| Exchange | SHG |
|---|---|
| CurrencyCode | CNY |
| Sector | Technology |
| Industry | Scientific & Technical Instruments |
| ISIN | CNE100002RS7 |
| Market Cap | 4B |
|---|---|
| PE Ratio | None |
| Target Price | None |
| Beta | 0.22 |
| Dividend Yield | None |
Qingdao Topscomm Communication Inc., together with its subsidiaries, engages in the power distribution network and fire alarm businesses in Mainland China and internationally. It offers AMI, arc detection, distribution automation, low-voltage carrier, photovoltaic inverter, smart water management, smart street lights, wire loss control, and 10kV power line communication products. The company also provides intelligent distribution solutions, AMI, smart distribution network, smart new energy, smart water management, and smart street lights solutions. Qingdao Topscomm Communication Inc. was founded in 2008 and is headquartered in Qingdao, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 603421.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