-
1 Comment
SK Securities Co., Ltd is currently in a long term uptrend where the price is trading 12.3% above its 200 day moving average.
From a valuation standpoint, the stock is 24.2% more expensive than other stocks from the Financial Services sector with a price to sales ratio of 1.7.
SK Securities Co., Ltd's total revenue rose by 21.0% to $70B since the same quarter in the previous year.
Its net income has increased by 149.2% to $7B since the same quarter in the previous year.
Finally, its free cash flow grew by 267.1% to $126B since the same quarter in the previous year.
Based on the above factors, SK Securities Co., Ltd gets an overall score of 4/5.
| Exchange | KO |
|---|---|
| CurrencyCode | KRW |
| ISIN | KR7001510007 |
| Sector | Financial Services |
| Industry | Capital Markets |
| Beta | 1.57 |
|---|---|
| Market Cap | 771B |
| PE Ratio | None |
| Target Price | None |
| Dividend Yield | None |
SK Securities Co., Ltd., a financial investment company, provides various financial services. It operates through Consignment trading, IB, Proprietary trading, and Savings banking segments. The company is involved in brokerage of consignment trading of securities and related business activities; corporate finance, business activities related to investment finance such as PF and PEF, and strategic investment activities; business activities of holding or trading securities and derivatives; and performance of the personal and corporate finance sectors of a major subsidiary savings bank. SK Securities Co., Ltd. was founded in 1955 and is based in Seoul, South Korea.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 001510.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 2026