-
1 Comment
IReader Technology Co., Ltd is currently in a long term downtrend where the price is trading 20.1% below its 200 day moving average.
From a valuation standpoint, the stock is 11.7% cheaper than other stocks from the Technology sector with a price to sales ratio of 7.1.
IReader Technology Co., Ltd's total revenue rose by 5.7% to $515M since the same quarter in the previous year.
Its net income has increased by 26.1% to $56M since the same quarter in the previous year.
Finally, its free cash flow grew by 341.5% to $171M since the same quarter in the previous year.
Based on the above factors, IReader Technology Co., Ltd gets an overall score of 4/5.
| Exchange | SHG |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE100002VN0 |
| Sector | Technology |
| Industry | Software - Application |
| Market Cap | 17B |
|---|---|
| PE Ratio | None |
| Beta | 1.01 |
| Target Price | 17.15 |
| Dividend Yield | 0.3% |
IReader Technology Co., Ltd. engages in the digital reading platform and copyright product business in China. The company edits and produces digital book content with publishing houses, copyright agencies, literary websites, and authors through digital reading platforms. It also offers the iReader app, an e-reading mobile app that contains a library of content, including published works, original literature, audiobooks, comics, and magazines; iReader Select, which provides digital libraries and reading solutions; iReader Bookstore, which offers comics; and Dejian Novel. The company was founded in 2008 and is based in Beijing, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 603533.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