-
1 Comment
Spic Dongfang Energy Corporation is currently in a long term downtrend where the price is trading 5.5% below its 200 day moving average.
From a valuation standpoint, the stock is 37.2% cheaper than other stocks from the Utilities sector with a price to sales ratio of 2.3.
Spic Dongfang Energy Corporation's total revenue rose by 364.6% to $3B since the same quarter in the previous year.
Its net income has increased by 632.7% to $286M since the same quarter in the previous year.
Finally, its free cash flow grew by 373.2% to $2B since the same quarter in the previous year.
Based on the above factors, Spic Dongfang Energy Corporation gets an overall score of 4/5.
Exchange | SHE |
---|---|
CurrencyCode | CNY |
ISIN | CNE000001154 |
Sector | Utilities |
Industry | Utilities - Regulated Electric |
Beta | 0.12 |
---|---|
Dividend Yield | 1.0% |
Target Price | 4.09 |
Market Cap | 35B |
PE Ratio | 36.0 |
SPIC Industry-Finance Holdings Co., Ltd. engages in the energy, trust, insurance, asset management, and other businesses in China. The company is involved in the power generation and heating; fund, movable property, and real estate trust; insurance, future, and property brokerage; and risk management and other businesses, as well as power related services. It also engages in the asset management, investment management, corporate management, investment consulting, and other activities. The company was formerly known as SPIC Dongfang Energy Corporation and changed its name to SPIC Industry-Finance Holdings Co., Ltd. in May 2022. The company was founded in 1998 and is based in Beijing, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 000958.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