-
1 Comment
China Everbright Water Limited is currently in a long term uptrend where the price is trading 7.6% above its 200 day moving average.
From a valuation standpoint, the stock is 53.1% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.8.
China Everbright Water Limited's total revenue rose by 234.8% to $6B since the same quarter in the previous year.
Its net income has increased by 344.6% to $1B since the same quarter in the previous year.
Finally, its free cash flow fell by 146.4% to $-314M since the same quarter in the previous year.
Based on the above factors, China Everbright Water Limited gets an overall score of 4/5.
ISIN | BMG2116Y1057 |
---|---|
Sector | Utilities |
Exchange | SG |
CurrencyCode | SGD |
Industry | Utilities - Regulated Water |
Target Price | 8.7 |
---|---|
Beta | 0.42 |
Market Cap | 672M |
PE Ratio | 3.92 |
Dividend Yield | 8.7% |
China Everbright Water Limited engages in the water environment management business in Mainland China and Germany. It is involved in municipal wastewater treatment, industrial wastewater treatment, water supply, reusable water, sludge treatment and disposal, sponge city construction, river-basin ecological restoration, livestock and poultry manure resources utilization; and leachate treatment, as well as research and development on water environmental technologies and engineering construction. The company was incorporated in 2003 and is based in Shenzhen, the People's Republic of China. China Everbright Water Limited is a subsidiary of China Everbright Environment Group Limited.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for U9E.SG 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