-
1 Comment
Shijiazhuang ChangShan BeiMing Technology Co., Ltd is currently in a long term uptrend where the price is trading 42.4% above its 200 day moving average.
From a valuation standpoint, the stock is 80.6% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.0.
Shijiazhuang ChangShan BeiMing Technology Co., Ltd's total revenue sank by 28.3% to $2B since the same quarter in the previous year.
Its net income has increased by 223.1% to $36M since the same quarter in the previous year.
Finally, its free cash flow fell by 242.8% to $-336M since the same quarter in the previous year.
Based on the above factors, Shijiazhuang ChangShan BeiMing Technology Co., Ltd gets an overall score of 3/5.
Sector | Consumer Cyclical |
---|---|
Industry | Textile Manufacturing |
Exchange | SHE |
CurrencyCode | CNY |
ISIN | CNE0000013X7 |
Market Cap | 41B |
---|---|
Target Price | 13.5 |
Beta | -0.04 |
PE Ratio | None |
Dividend Yield | None |
Shijiazhuang ChangShan BeiMing Technology Co.,Ltd manufactures and sells textile products in China. The company offers yarns, fabrics, clothing, home textiles, and industrial textiles. It also operates a cloud data center; provides consulting, implementation, operation, and maintenance services for smart cities; and operates an online dispute resolution platform. The company was formerly known as Shijiazhuang Changshan Textile Company Limited and changed its name to Shijiazhuang ChangShan BeiMing Technology Co.,Ltd in October 2017. Shijiazhuang ChangShan BeiMing Technology Co.,Ltd was founded in 1998 and is based in Shijiazhuang, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 000158.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