-
1 Comment
PR TIMES, Inc is currently in a long term uptrend where the price is trading 2.3% above its 200 day moving average.
From a valuation standpoint, the stock is 472.2% more expensive than other stocks from the Communication Services sector with a price to sales ratio of 15.0.
PR TIMES, Inc's total revenue rose by 30.0% to $1B since the same quarter in the previous year.
Its net income has increased by 166.9% to $324M since the same quarter in the previous year.
Based on the above factors, PR TIMES, Inc gets an overall score of 3/5.
ISIN | JP3801050000 |
---|---|
Exchange | TSE |
CurrencyCode | JPY |
Sector | Communication Services |
Industry | Internet Content & Information |
Market Cap | 31B |
---|---|
PE Ratio | 26.45 |
Target Price | 3800 |
Dividend Yield | 1.0% |
Beta | 0.4 |
PR TIMES Corporation operates PR TIMES platform that connects companies, media, and consumer with news in Japan. It also offers Jooto, a task and project management tool; Tayori, a cloud information organization tool; Web clipping services that can extract and analyze articles containing specified keywords from domestic news media; PR TIMES LIVE, which offers online reporting by live streaming press events; PR TIMES TV, a video PR service; and PR Times and PR Times Story. The company operates media, such as BRIDGE, isuta, U-NOTE, Techable, STRAIGHT PRESS, IGNITE, PR EDGE, and PR TIMES magazine to deliver information about people of action world. Further, it offers PR strategy/planning to material creation, and media relations. PR TIMES, Inc. was incorporated in 2005 and is based in Tokyo, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 3922.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