-
1 Comment
Papa John's International, Inc is currently in a long term uptrend where the price is trading 16.2% above its 200 day moving average.
From a valuation standpoint, the stock is 97.4% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.6.
Papa John's International, Inc's total revenue rose by 12.5% to $470M since the same quarter in the previous year.
Its net income has increased by 714.7% to $13M since the same quarter in the previous year.
Finally, its free cash flow grew by 310.4% to $7M since the same quarter in the previous year.
Based on the above factors, Papa John's International, Inc gets an overall score of 5/5.
Exchange | F |
---|---|
ISIN | US6988131024 |
CurrencyCode | EUR |
Sector | Consumer Cyclical |
Industry | Restaurants |
Beta | 1.25 |
---|---|
Target Price | 128.5 |
Dividend Yield | 6.1% |
Market Cap | 931M |
PE Ratio | 12.61 |
Papa John's International, Inc. operates and franchises pizza delivery and carryout restaurants under the Papa Johns trademark in the United States, Canada, and internationally. It operates through four segments: Domestic Company-Owned Restaurants, North America Franchising, North America Commissaries, and International. The company also operates dine-in and delivery restaurants under the Papa Johns trademark internationally. It offers pizza and other food and beverage products. In addition, the company supplies pizza sauce, dough, food products, paper products, smallware, and cleaning supplies to restaurants. Papa John's International, Inc. was founded in 1984 and is based in Louisville, Kentucky.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for PP1.F 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