-
| Exchange | SG |
|---|---|
| CurrencyCode | SGD |
| ISIN | SG1DG8000009 |
| Sector | Industrials |
| Industry | Waste Management |
| Dividend Yield | 0.7% |
|---|---|
| Market Cap | 104M |
| PE Ratio | 30.5 |
| Target Price | 0.46 |
| Beta | 0.57 |
Sanli Environmental Limited operates as an environmental engineering company in the field of water and waste management in Singapore, Myanmar, Malaysia, and Thailand. It operates through three segments: Engineering, Procurement and Construction (EPC); Operations and Maintenance (O&M); and Emerging Business Segments (EBS). The EPC segment provides engineering, procurement, and construction services, including process upgrading of existing water treatment plants, upgrading of pumping station capacities, replacement of aged mechanical and electrical equipment, designing and building various treatment process systems in the field of water and waste management, air pollution control, and industrial systems. Its O&M segment provides corrective and preventive maintenance services to ensure reliability and minimal disruptions to customers' operations. The Emerging Business Segments (EBS) segment produces and supplies magnesium hydroxide slurry for wastewater treatment, flue gas desulphurisation, and other industrial processes; integrated environmental engineering solutions for industrial facilities, as well as engages in the development, ownership, and operation of solar power assets. Sanli Environmental Limited was founded in 2006 and is headquartered in Singapore.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 1E3.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 2026