-
1 Comment
Laox CO., LTD is currently in a long term uptrend where the price is trading 40.0% above its 200 day moving average.
From a valuation standpoint, the stock is 81.4% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.2.
Laox CO., LTD's total revenue sank by 29.8% to $24B since the same quarter in the previous year.
Its net income has increased by 29.3% to $-3B since the same quarter in the previous year.
Based on the above factors, Laox CO., LTD gets an overall score of 3/5.
| Exchange | TSE |
|---|---|
| CurrencyCode | JPY |
| ISIN | JP3967000005 |
| Sector | Consumer Cyclical |
| Industry | Specialty Retail |
| Dividend Yield | 2.0% |
|---|---|
| Beta | -0.12 |
| Market Cap | 13B |
| Target Price | 710 |
| PE Ratio | None |
Laox Holdings CO.,LTD. primarily engages in the retail business. It operates through four reportable segments: Gift Solutions Business, Retail Business, Trading Business, and Asset Service Business segments. The company engages in the sales business of gift items and lifestyle-related goods; and operation of duty-free shops for tourists visiting Japan, as well as sales of men's, women's clothing, and general merchandise. It is also involved in trading business through import and export of private label products and develops global e-commerce; and operation of Japanese restaurants. In addition, it engages in the operation and management of mixed-use commercial facilities, real estate sales and brokerage, and rental property management. Laox Holdings CO.,LTD. was founded in 1930 and is headquartered in Minato, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 8202.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