-
1 Comment
Annaly Capital Management, Inc is currently in a long term uptrend where the price is trading 4.6% above its 200 day moving average.
From a valuation standpoint, the stock is 100.0% cheaper than other stocks from the Real Estate sector with a price to sales ratio of 0.0.
Annaly Capital Management, Inc's total revenue sank by 28.1% to $897M since the same quarter in the previous year.
Its net income has dropped by 27.5% to $877M since the same quarter in the previous year.
Finally, its free cash flow fell by 671.9% to $-7B since the same quarter in the previous year.
Based on the above factors, Annaly Capital Management, Inc gets an overall score of 2/5.
| Exchange | F |
|---|---|
| CurrencyCode | EUR |
| ISIN | None |
| Sector | Real Estate |
| Industry | REIT - Mortgage |
| Market Cap | 2B |
|---|---|
| Beta | 1.21 |
| PE Ratio | 0.59 |
| Target Price | 8.95 |
| Dividend Yield | 58.% |
Annaly Capital Management, Inc., a diversified capital manager, engages in mortgage finance and corporate middle market lending. The company invests in agency mortgage-backed securities, mortgage servicing rights, Agency commercial mortgage-backed securities, non-Agency residential mortgage assets, residential mortgage loans, credit risk transfer securities, corporate debts, and other commercial real estate investments. It has elected to be taxed as a real estate investment trust (REIT). As a REIT, it is not subject to federal income tax to the extent that it distributes its taxable income to its shareholders. The company was founded in 1996 and is based in New York, New York.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for AAY.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
