-
1 Comment
Shinsegae Inc is currently in a long term uptrend where the price is trading 6.5% above its 200 day moving average.
From a valuation standpoint, the stock is 59.3% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.6.
Shinsegae Inc's total revenue sank by 24.0% to $1T since the same quarter in the previous year.
Its net income has increased by 106.4% to $12B since the same quarter in the previous year.
Finally, its free cash flow grew by 150.1% to $145B since the same quarter in the previous year.
Based on the above factors, Shinsegae Inc gets an overall score of 4/5.
Sector | Consumer Cyclical |
---|---|
Industry | Department Stores |
ISIN | KR7004170007 |
Exchange | KO |
CurrencyCode | KRW |
Market Cap | 1T |
---|---|
PE Ratio | None |
Target Price | 168000 |
Dividend Yield | 3.0% |
Beta | 0.53 |
SHINSEGAE Inc. operates department stores in South Korea. The company operates through Department Store, Wholesale and Retail Industry, Real Estate Industry, Hospitality, Duty-Free Store, and Others segments. The company also manufactures and retails clothing and furniture; manufactures, retails, and distributes cosmetics; produces and supplies broadcast programs; develops and leases real estate properties; offers advisory and online retail services; operates passenger terminals and duty-free stores; and engages in the information and communication, financial investment, and hotel businesses. SHINSEGAE Inc. was founded in 1955 and is headquartered in Seoul, South Korea.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 004170.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