-
1 Comment
S Line Co.,Ltd is currently in a long term uptrend where the price is trading 1.6% above its 200 day moving average.
From a valuation standpoint, the stock is 82.5% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.2.
S Line Co.,Ltd's total revenue sank by 0.1% to $13B since the same quarter in the previous year.
Its net income has increased by 130.2% to $458M since the same quarter in the previous year.
Based on the above factors, S Line Co.,Ltd gets an overall score of 3/5.
Exchange | TSE |
---|---|
CurrencyCode | JPY |
Sector | Industrials |
Industry | Trucking |
ISIN | JP3164000006 |
Market Cap | 16B |
---|---|
PE Ratio | 0.0 |
Target Price | None |
Dividend Yield | 1.9% |
Beta | 0.48 |
S Line Group Co., Ltd. provides transportation services in Japan. Its services include small cargo/swallow delivery, chartered cargo/charter flight, large product home delivery, heavy goods transportation, overseas transportation, and swallow moving services. The company also provides 3PL and logistics information system solutions; and storage and processing, vehicle maintenance, and information system services, as well as delivers gift items from the farm. In addition, it offers air conditioning work, antenna installation, electric water heater installation, branch faucets and air toilet seat installation, dishwasher installation, and furniture and other home appliance installation services. The company was formerly known as S Line Co.,Ltd. and changed its name to S Line Group Co., Ltd. in July 2023. The company was founded in 1938 and is based in Hashima, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 9078.TSE 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