-
1 Comment
Futaba Corporation is currently in a long term downtrend where the price is trading 13.7% below its 200 day moving average.
From a valuation standpoint, the stock is 72.8% cheaper than other stocks from the Technology sector with a price to sales ratio of 0.9.
Futaba Corporation's total revenue sank by 13.0% to $13B since the same quarter in the previous year.
Its net income has dropped by 24.8% to $-937M since the same quarter in the previous year.
Based on the above factors, Futaba Corporation gets an overall score of 1/5.
| Industry | Electronic Components |
|---|---|
| Exchange | TSE |
| Sector | Technology |
| CurrencyCode | JPY |
| ISIN | JP3824400000 |
| PE Ratio | 98.49 |
|---|---|
| Target Price | 2060 |
| Dividend Yield | 0.0% |
| Beta | 0.22 |
| Market Cap | 28B |
Futaba Corporation, together with its subsidiaries, designs, develops, manufactures, and sells electronic equipment, radio control, and manufacturing equipment in Japan, the United States, Europe, rest of Asia, and internationally. It operates through Electronic Systems; and Machinery and Tooling segments. The Electronic Systems segment comprises composite modules, radio control equipment for industrial and hobby, robotics products for drones and servos, organic light-emitting diode, touch panels, and VFDs, as well as industrial servos and transmitters. Its Machinery and Tooling segment consists of press die set components, mold base components, and precision plates, as well as equipment for automation and streamlining molding works. Futaba Corporation was incorporated in 1948 and is headquartered in Mobara, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 6986.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 2026