-
1 Comment
UTour Group Co., Ltd is currently in a long term downtrend where the price is trading 14.5% below its 200 day moving average.
From a valuation standpoint, the stock is 74.7% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.3.
UTour Group Co., Ltd's total revenue sank by 95.8% to $128M since the same quarter in the previous year.
Its net income has dropped by 195.9% to $-136M since the same quarter in the previous year.
Finally, its free cash flow fell by 398.0% to $-44M since the same quarter in the previous year.
Based on the above factors, UTour Group Co., Ltd gets an overall score of 1/5.
| Sector | Consumer Cyclical |
|---|---|
| Industry | Travel Services |
| ISIN | CNE100001RH2 |
| CurrencyCode | CNY |
| Exchange | SHE |
| Target Price | 6 |
|---|---|
| PE Ratio | None |
| Market Cap | 10B |
| Dividend Yield | 0.0% |
| Beta | 0.97 |
UTour Group Co., Ltd. engages in outbound tourism wholesale and retail business in China and internationally. It provides study tours, immigration and real estate, tourism finance, health care, etc., and air ticket sales agency services. The company also provides integrated marketing; investment and asset management; currency exchange; internet financial information; and monetary financial services. It operates through a network of 737 retail stores. The company was formerly known as Beijing UTour International Travel Service Co., Ltd. and changed its name to UTour Group Co., Ltd. in July 2016. UTour Group Co., Ltd. was founded in 1992 and is headquartered in Beijing, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002707.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 2024
