-
1 Comment
DyDo Group Holdings, Inc is currently in a long term downtrend where the price is trading 5.6% below its 200 day moving average.
From a valuation standpoint, the stock is 52.4% cheaper than other stocks from the Consumer Defensive sector with a price to sales ratio of 0.5.
DyDo Group Holdings, Inc's total revenue rose by 19.4% to $45B since the same quarter in the previous year.
Its net income has increased by 403.8% to $3B since the same quarter in the previous year.
Based on the above factors, DyDo Group Holdings, Inc gets an overall score of 3/5.
| Exchange | TSE |
|---|---|
| CurrencyCode | JPY |
| ISIN | JP3488400007 |
| Sector | Consumer Defensive |
| Industry | Beverages - Non-Alcoholic |
| PE Ratio | None |
|---|---|
| Target Price | 2100 |
| Dividend Yield | 1.0% |
| Market Cap | 92B |
| Beta | -0.13 |
DyDo Group Holdings, Inc. plans and develops beverages for beverage manufacturers in Japan and internationally. The company offers coffee, tea, carbonated drink, mineral water, and juice based products, as well as other products, such as soups and sweet bean porridge. It also exports milk coffee, brewed black, and brewed latte products. In addition, the company is involved in the provision of Chinese products, such as Barley Tea and Black Tea; OEM production of energy drinks; and offers fruit dessert jelly products. It sells its products under the DyDo, Saka, and Maltana brands. The company was formerly known as DyDo DRINCO, INC. and changed its name to DyDo Group Holdings, Inc. in January 2017. DyDo Group Holdings, Inc. was founded in 1947 and is headquartered in Kita, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 2590.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
