-
1 Comment
Mitsuchi Corporation is currently in a long term uptrend where the price is trading 8.8% above 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.
Mitsuchi Corporation's total revenue sank by 1.9% to $3B since the same quarter in the previous year.
Its net income has increased by 18.1% to $78M since the same quarter in the previous year.
Finally, its free cash flow grew by 141.1% to $158M since the same quarter in the previous year.
Based on the above factors, Mitsuchi Corporation gets an overall score of 4/5.
Sector | Consumer Cyclical |
---|---|
Industry | Auto Parts |
Exchange | TSE |
CurrencyCode | JPY |
ISIN | JP3895100000 |
Market Cap | 3B |
---|---|
PE Ratio | 12.66 |
Target Price | None |
Dividend Yield | 3.1% |
Beta | -0.18 |
Mitsuchi Corporation manufactures, delivers, and sells custom fasteners for automotive components in Japan. The company offers engines, seats, powertrains, steering, rear-door locks, airbags, brakes, window regulators, undercarriage, and suspension systems; cold-forged products, including deformation, hole machining, gear processing, hole and gear processing, and forming and forging products. It also provides assembled products for window regulators and rear-door locks; and sun quick nuts, all quick nutters, and quick joints. The company was formerly known as Mitsuchi Byora Co., Ltd. and changed its name to Mitsuchi Corporation in February 1975. Mitsuchi Corporation was incorporated in 1963 and is headquartered in Kasugai, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 3439.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