-
1 Comment
Lingyi iTech (Guangdong) Company is currently in a long term downtrend where the price is trading 13.5% below its 200 day moving average.
From a valuation standpoint, the stock is 72.6% cheaper than other stocks from the Technology sector with a price to sales ratio of 2.2.
Lingyi iTech (Guangdong) Company's total revenue rose by 12.9% to $9B since the same quarter in the previous year.
Its net income has increased by 501.8% to $824M since the same quarter in the previous year.
Finally, its free cash flow grew by 12.4% to $453M since the same quarter in the previous year.
Based on the above factors, Lingyi iTech (Guangdong) Company gets an overall score of 4/5.
Exchange | SHE |
---|---|
CurrencyCode | CNY |
Sector | Technology |
Industry | Electronic Components |
ISIN | CNE1000015L5 |
Market Cap | 112B |
---|---|
Beta | 0.94 |
PE Ratio | 56.86 |
Target Price | 15.72 |
Dividend Yield | 0.3% |
Lingyi iTech (Guangdong) Company provides smart manufacturing services and solutions in China and internationally. The company provides electric heating, battery power, and thermal management (heat dissipation) solutions; as well as AI mobile phones and folding screen mobile phones; AIPC and tablet computers; image display; materials; AI glasses and XR wearable devices; boutique assembly; sensors and related modules; and robots and other related hardware products. The company was founded in 1975 and is based in Jiangmen, China. Lingyi iTech (Guangdong) Company is a subsidiary of Lingsheng Investment (Jiangsu) Co., Ltd.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002600.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