-
1 Comment
Eternal Asia Supply Chain Management Ltd is currently in a long term uptrend where the price is trading 14.7% above its 200 day moving average.
From a valuation standpoint, the stock is 98.0% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.1.
Eternal Asia Supply Chain Management Ltd's total revenue sank by 39.1% to $15B since the same quarter in the previous year.
Its net income has increased by 8.1% to $21M since the same quarter in the previous year.
Finally, its free cash flow grew by 72.7% to $848M since the same quarter in the previous year.
Based on the above factors, Eternal Asia Supply Chain Management Ltd gets an overall score of 4/5.
Exchange | SHE |
---|---|
CurrencyCode | CNY |
Sector | Industrials |
Industry | Specialty Business Services |
ISIN | CNE1000007Y5 |
PE Ratio | 115.0 |
---|---|
Target Price | 5.76 |
Dividend Yield | 0.3% |
Beta | 0.72 |
Market Cap | 12B |
Eternal Asia Supply Chain Management Ltd. engages in supply chain and industrial chain businesses in China. The company provides key account 1 + N, internet marketing, integration operation of procurement and sales, cross-border business and logistics, enterprise digitization, and government and enterprise procurement. It offers industrial chain services, including infrastructure raw materials, new energy, food, agriculture, forestry, semiconductor, big consumption, medical care, electronic information, and other services; and investment, financing, and incubation services. The company was founded in 1997 and is based in Shenzhen, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002183.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