-
1 Comment
Yasunaga Corporation is currently in a long term downtrend where the price is trading 5.9% below its 200 day moving average.
From a valuation standpoint, the stock is 53.6% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.5.
Yasunaga Corporation's total revenue rose by 6.9% to $9B since the same quarter in the previous year.
Its net income has increased by 1606.7% to $226M since the same quarter in the previous year.
Based on the above factors, Yasunaga Corporation gets an overall score of 3/5.
Exchange | TSE |
---|---|
CurrencyCode | JPY |
Sector | Consumer Cyclical |
Industry | Auto Parts |
ISIN | JP3932850005 |
PE Ratio | 12.33 |
---|---|
Target Price | None |
Dividend Yield | 2.7% |
Beta | 0.79 |
Market Cap | 6B |
Yasunaga Corporation manufactures and sells engine parts and machine tools, and wire saw and electronics systems. It provides automotive and industrial machinery comprising engine parts, such as connecting rods, cylinder heads and blocks, camshafts, crankshafts, oil pans, bearing caps, flywheel housing, balance shaft, hydraulic lash adjuster, exhaust manifold, throttle body, casting parts, and converter housing, as well as inverter, transaxle, motor stator, and brake actuator housing parts; machine tools, solar cells, wire saw machines, inspection and measuring machines, and assembly machines; and environmental equipment comprising air pumps and disposers. The company was formerly known as Yasunaga Tekkosho Co., Ltd. and changed its name to Yasunaga Corporation in April 1988. Yasunaga Corporation was founded in 1923 and is based in Iga, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 7271.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