-
1 Comment
International Paper Company is currently in a long term uptrend where the price is trading 15.5% above its 200 day moving average.
From a valuation standpoint, the stock is 98.9% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.0.
International Paper Company's total revenue sank by 4.7% to $5B since the same quarter in the previous year.
Its net income has dropped by 7.3% to $153M since the same quarter in the previous year.
Finally, its free cash flow grew by 23.0% to $695M since the same quarter in the previous year.
Based on the above factors, International Paper Company gets an overall score of 3/5.
| Sector | Consumer Cyclical |
|---|---|
| Industry | Packaging & Containers |
| Exchange | NYSE |
| CurrencyCode | USD |
| ISIN | US4601461035 |
| Market Cap | 19B |
|---|---|
| Dividend Yield | 5.2% |
| Beta | 1.04 |
| PE Ratio | None |
| Target Price | 46.47 |
International Paper Company produces and sells renewable fiber-based packaging in North America, Latin America, Europe, South America, and North Africa. It operates through two segments, Packaging Solutions North America and Packaging Solutions EMEA. The company offers linerboard, medium, whitetop, and saturating kraft; and converts containerboard into corrugated boxes, bulk bins, shipping containers and specialty packaging through its converting facilities. Its products support customers in various industries, such as food and beverage, agriculture, industrial manufacturing, personal care pharmaceuticals and consumer goods. The company was founded in 1898 and is headquartered in Memphis, Tennessee.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for IP 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