-
1 Comment
Nations Technologies Inc is currently in a long term uptrend where the price is trading 105.7% above its 200 day moving average.
From a valuation standpoint, the stock is 48.1% more expensive than other stocks from the Technology sector with a price to sales ratio of 11.9.
Nations Technologies Inc's total revenue rose by 19.3% to $106M since the same quarter in the previous year.
Its net income has increased by 166.2% to $26M since the same quarter in the previous year.
Finally, its free cash flow grew by 153.9% to $40M since the same quarter in the previous year.
Based on the above factors, Nations Technologies Inc gets an overall score of 4/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| Sector | Technology |
| Industry | Semiconductors |
| ISIN | CNE100000NT8 |
| Beta | -0.92 |
|---|---|
| Market Cap | 15B |
| PE Ratio | None |
| Target Price | 12.85 |
| Dividend Yield | None |
Nsing Technologies Inc. provides integrated circuit (IC) products and services in China and internationally. It offers MCU products; power products; micro authentication, computing, and security chips; and Bluetooth wireless RF chips. The company's products are used in consumer electronics, medical electronics, home appliances, digital power, automotive electronics, internet of things, and industrial electronics applications. The company was formerly known as Nations Technologies Inc. and changed its name to Nsing Technologies Inc. in September 2025. Nsing Technologies Inc. was founded in 2000 and is headquartered in Shenzhen, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 300077.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
