-
1 Comment
AuBEX CORPORATION is currently in a long term uptrend where the price is trading 5.6% above its 200 day moving average.
From a valuation standpoint, the stock is 62.9% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.4.
AuBEX CORPORATION's total revenue sank by 11.1% to $1B since the same quarter in the previous year.
Its net income has dropped by 215.0% to $-61M since the same quarter in the previous year.
Based on the above factors, AuBEX CORPORATION gets an overall score of 2/5.
ISIN | JP3173600002 |
---|---|
Exchange | TSE |
CurrencyCode | JPY |
Sector | Consumer Cyclical |
Industry | Department Stores |
Market Cap | 4B |
---|---|
PE Ratio | 7.64 |
Target Price | None |
Dividend Yield | 2.0% |
Beta | -0.06 |
AuBEX CORPORATION manufactures and sells nibs and medical equipment in Japan and internationally. The company offers nibs made from polyester fibers, nylon fibers, acrylic fibers, plastics, and engineering plastics for stationery used in writing, marking, painting, and presentation, as well as for PC peripherals and industrial equipment; and nibs for makeup and cosmetics products, including porous tips and PBT brush tips, feeders, and cosmetics tips. It also provides medical equipment and components, such as pressure infusion devices and angiography guide wires for public and private university hospitals, and other hospitals. The company was formerly known as Tokyo hat Co., Ltd. and changed its name to AuBEX CORPORATION in 1985. AuBEX CORPORATION was founded in 1892 and is headquartered in Tokyo, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 3583.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