-
1 Comment
LuckLand Co., Ltd is currently in a long term uptrend where the price is trading 11.7% above its 200 day moving average.
From a valuation standpoint, the stock is 38.8% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.7.
LuckLand Co., Ltd's total revenue sank by 29.1% to $10B since the same quarter in the previous year.
Its net income has dropped by 159.1% to $-358M since the same quarter in the previous year.
Based on the above factors, LuckLand Co., Ltd gets an overall score of 2/5.
| Sector | Industrials |
|---|---|
| Industry | Engineering & Construction |
| Exchange | TSE |
| CurrencyCode | JPY |
| ISIN | JP3968000004 |
| Beta | 0.26 |
|---|---|
| Market Cap | 17B |
| PE Ratio | 7.57 |
| Target Price | 1800 |
| Dividend Yield | 1.3% |
LuckLand Co., Ltd. engages in the research, planning and development, design, construction, supervision, and maintenance services of commercial facilities, retail and food service establishments, logistics facilities, food factories, and hotels. The company is involved in the shop facility construction business comprising site survey, building equipment survey, planning, design, and construction; commercial facility construction business, including building equipment, interior decoration supervision, large store site law adjustment, equipment design, and construction; food factory/logistics warehouse construction business; environmental sector business; and construction, building equipment, and refrigeration equipment businesses. LuckLand Co., Ltd. was incorporated in 1970 and is headquartered in Shinjuku, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 9612.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