-
1 Comment
Taekwang Industrial Co., Ltd is currently in a long term uptrend where the price is trading 13.0% above its 200 day moving average.
From a valuation standpoint, the stock is 1.3% more expensive than other stocks from the Energy sector with a price to sales ratio of 0.5.
Taekwang Industrial Co., Ltd's total revenue sank by 39.1% to $412B since the same quarter in the previous year.
Its net income has increased by 5.0% to $-40B since the same quarter in the previous year.
Finally, its free cash flow fell by 134.5% to $-11B since the same quarter in the previous year.
Based on the above factors, Taekwang Industrial Co., Ltd gets an overall score of 2/5.
Industry | Chemicals |
---|---|
CurrencyCode | KRW |
Exchange | KO |
ISIN | KR7003240009 |
Sector | Basic Materials |
Beta | 0.8 |
---|---|
Market Cap | 608B |
PE Ratio | None |
Dividend Yield | 0.2% |
Target Price | 999999.9999 |
Taekwang Industrial Co., Ltd. engages in the synthetic fiber, textile, petrochemical, and advanced material businesses in South Korea and internationally. It offers synthetic fibers comprising acrylic fibers, nylon filaments, spandex, and low-melting-point fibers, as well as ring, open-end, acrylic, and acrylic blended spun yarns. The company also provides petrochemical products, including purified terephthalic acids, propylene, acrylonitrile, sodium cyanide, acetonitrile, ammonium sulphate, and hydrogen peroxide. In addition, it offers tricot and polyester fabrics; and advanced materials, such as carbon and aramid fibers. The company was founded in 1950 and is headquartered in Seoul, South Korea.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 003240.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 2024