-
1 Comment
Korea Electric Power Industrial Development Co., Ltd is currently in a long term uptrend where the price is trading 217.6% above its 200 day moving average.
From a valuation standpoint, the stock is 5.3% more expensive than other stocks from the Utilities sector with a price to sales ratio of 0.5.
Korea Electric Power Industrial Development Co., Ltd's total revenue sank by 3.0% to $105B since the same quarter in the previous year.
Its net income has increased by 1.8% to $-6B since the same quarter in the previous year.
Finally, its free cash flow grew by 176.8% to $16B since the same quarter in the previous year.
Based on the above factors, Korea Electric Power Industrial Development Co., Ltd gets an overall score of 3/5.
Exchange | KO |
---|---|
CurrencyCode | KRW |
ISIN | KR7130660004 |
Sector | Utilities |
Industry | Utilities - Regulated Electric |
Market Cap | 376B |
---|---|
Beta | 0.82 |
PE Ratio | None |
Target Price | None |
Dividend Yield | 3.4% |
Korea Electric Power Industrial Development Co., Ltd. engages in the operation and maintenance of thermal power generation facilities, metering, and renewable energy businesses in South Korea. The company also engages in the mining development, coal terminal O&M, building management, and solar power business. In addition, it operates energy power generation plants. The company was formerly known as Hansung Global Industry Co., Ltd. and changed its name to Korea Electric Power Industrial Development Co., Ltd. in February 1996. Korea Electric Power Industrial Development Co., Ltd. was founded in 1990 and is headquartered in Seoul, South Korea.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 130660.KO 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