-
1 Comment
Hunan Friendship&Apollo Commercial Co.,Ltd is currently in a long term downtrend where the price is trading 6.2% below its 200 day moving average.
From a valuation standpoint, the stock is 84.4% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.8.
Hunan Friendship&Apollo Commercial Co.,Ltd's total revenue rose by 8.0% to $1B since the same quarter in the previous year.
Its net income has increased by 12.1% to $85M since the same quarter in the previous year.
Finally, its free cash flow grew by 87.2% to $-25M since the same quarter in the previous year.
Based on the above factors, Hunan Friendship&Apollo Commercial Co.,Ltd gets an overall score of 4/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE100000F12 |
| Sector | Consumer Cyclical |
| Industry | Department Stores |
| Market Cap | 8B |
|---|---|
| Beta | 0.19 |
| Target Price | 3.6 |
| Dividend Yield | 0.3% |
| PE Ratio | 111.6 |
Hunan Friendship&Apollo Commercial Co.,Ltd. operates department stores in China. The operates outlets; shopping centers; specialty stores; and online shopping platforms comprising Youa Overseas Shopping, Youa Weidian, and Youa Shopping, as well as leases properties. It operates stores and properties under the Friendship Store AB Hall, Friendship Mall, Apollo Commercial Plaza, Changsha Youa Outlets, Chenzhou Youa International Plaza, Changde Youa International Plaza, Shaoyang Youa International Plaza, etc. names. Hunan Friendship&Apollo Commercial Co.,Ltd. was founded in 2004 and is headquartered in Changsha, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002277.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
