-
1 Comment
MT Genex Corporation is currently in a long term downtrend where the price is trading 6.7% below its 200 day moving average.
From a valuation standpoint, the stock is 21.3% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.9.
MT Genex Corporation's total revenue rose by 50.4% to $847M since the same quarter in the previous year.
Its net income has increased by 111.6% to $65M since the same quarter in the previous year.
Based on the above factors, MT Genex Corporation gets an overall score of 3/5.
| Industry | Specialty Business Services |
|---|---|
| Exchange | TSE |
| CurrencyCode | JPY |
| ISIN | JP3297300000 |
| Sector | Industrials |
| PE Ratio | 14.25 |
|---|---|
| Target Price | None |
| Dividend Yield | 1.0% |
| Market Cap | 4B |
| Beta | 0.06 |
MT Genex Corporation, together with its subsidiaries, engages in renovation of office buildings and real estate management in Japan. It operates through four segments: Renovation, Parking Lots, Facility Maintenance and Management, and Insurance Agency. The company is involved in operation and management of parking lots; proposal and construction of energy-saving LED for office lighting in the renovation work of office buildings and hotels, etc.; and building management, equipment management, cleaning, security, office work, ordering of toilet paper and other hygiene consumables, inspection of fire prevention objects, and operation and management of vending machines. The company was founded in 1945 and is headquartered in Tokyo, Japan. MT Genex Corporation operates as a subsidiary of Mori Trust Co., Ltd.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 9820.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