-
1 Comment
Hi-Lex Corporation is currently in a long term uptrend where the price is trading 13.7% above its 200 day moving average.
From a valuation standpoint, the stock is 73.8% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.3.
Hi-Lex Corporation's total revenue sank by 2.8% to $58B since the same quarter in the previous year.
Its net income has increased by 158.4% to $2B since the same quarter in the previous year.
Based on the above factors, Hi-Lex Corporation gets an overall score of 3/5.
CurrencyCode | JPY |
---|---|
ISIN | JP3699600007 |
Sector | Industrials |
Industry | Conglomerates |
Exchange | TSE |
Beta | 0.46 |
---|---|
Market Cap | 58B |
Target Price | None |
PE Ratio | 26.14 |
Dividend Yield | 3.0% |
Hi-Lex Corporation operates in automotive, industrial equipment, and medical equipment businesses in Japan and internationally. The company provides system product, such as power lift gate, wheelchair anchoring, and electronic parking systems; door modules and window regulators; cables, including push-pull, pull, SPIRAX, and actuators; and ECU electronic control. It also offers accelerator actuator; housing equipment comprising damper, elevated grille, operator unit, and drain valve cable; operation box; and bath assist products. In addition, the company provides medical devices, including microcatheters, guidewires, vascular grafts, and other medical device parts, such as endoscope components, various catheter shafts, and cannula. Hi-Lex Corporation was founded in 1946 and is headquartered in Takarazuka, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 7279.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