-
1 Comment
Keiyo Co., Ltd is currently in a long term uptrend where the price is trading 7.7% above its 200 day moving average.
From a valuation standpoint, the stock is 62.9% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.4.
Keiyo Co., Ltd's total revenue sank by 4.9% to $26B since the same quarter in the previous year.
Its net income has increased by 738.8% to $562M since the same quarter in the previous year.
Based on the above factors, Keiyo Co., Ltd gets an overall score of 3/5.
Exchange | TSE |
---|---|
CurrencyCode | JPY |
ISIN | JP3277400002 |
Sector | Consumer Cyclical |
Industry | Home Improvement Retail |
PE Ratio | 23.37 |
---|---|
Target Price | None |
Beta | 0.08 |
Market Cap | 76B |
Dividend Yield | 1.0% |
Keiyo Co., Ltd. operates and manages a chain of home center stores in Japan. Its home center stores sell home improvement supplies including gardening tools, products, and plants; DIY materials, interior furnishing, wood materials, hardware/tools, building materials, paint, automotive related goods, leisure goods, soft and hard furnishings, pet products, kitchen supplies, tableware, bathroom supplies, cleaning goods, clothing, household goods, health and beauty goods, curtains, lighting products, and household and home electronics. The company was formerly known as Keiyo Industrial Co., Ltd. and changed its name to Keiyo Co., Ltd. in April 1979. Keiyo Co., Ltd. was incorporated in 1952 and is headquartered in Chiba, Japan. As of November 14, 2023, Keiyo Co., Ltd. operates as a subsidiary of DCM Holdings Co., Ltd.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 8168.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