-
1 Comment
Changsha Tongcheng Holdings Co.,Ltd is currently in a long term downtrend where the price is trading 2.3% 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.
Changsha Tongcheng Holdings Co.,Ltd's total revenue sank by 6.9% to $702M since the same quarter in the previous year.
Its net income has increased by 8.3% to $70M since the same quarter in the previous year.
Finally, its free cash flow grew by 228.1% to $172M since the same quarter in the previous year.
Based on the above factors, Changsha Tongcheng Holdings Co.,Ltd gets an overall score of 3/5.
| Sector | Consumer Cyclical |
|---|---|
| Industry | Department Stores |
| Exchange | SHE |
| CurrencyCode | CNY |
| ISIN | CNE000000LL0 |
| Beta | 0.54 |
|---|---|
| Market Cap | 3B |
| Target Price | 10.27 |
| Dividend Yield | 2.0% |
| PE Ratio | 21.54 |
Changsha Tongcheng Holdings Co.Ltd engages in commercial retail, comprehensive investment, and tourism hotels businesses in China. The company's commercial retail operation includes shopping centers, department stores, electrical appliances chains, and online professional platforms, as well as offers professional warehousing logistics distribution services. It also provides pawn, small loan, commercial factoring, and consignment services. In addition, the company is involved in the property leasing, property management, and investment activities; and tourism and hotel businesses. The company was founded in 1996 and is headquartered in Changsha, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 000419.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
