-
Sector | Real Estate |
---|---|
Industry | REIT - Specialty |
Exchange | NASDAQ |
CurrencyCode | USD |
ISIN | US3765492000 |
Market Cap | 228M |
---|---|
PE Ratio | None |
Target Price | None |
Dividend Yield | 7.7% |
Beta | 1.15 |
Founded in 1997, Gladstone Land is a publicly traded real estate investment trust that acquires and owns farmland and farm-related properties located in major agricultural markets in the U.S. The Company currently owns 150 farms, comprised of approximately 103,000 acres in 15 different states and over 55,000 acre-feet of water assets in California. Gladstone Land's farms are predominantly located in regions where its tenants are able to grow fresh produce annual row crops, such as berries and vegetables, which are generally planted and harvested annually. The Company also owns farms growing permanent crops, such as almonds, blueberries, figs, olives, pistachios, and wine grapes, which are generally planted every 20-plus years and harvested annually. Over 30% of the Company's fresh produce acreage is either organic or in transition to become organic, and nearly 20% of its permanent crop acreage falls into this category. The Company may also acquire property related to farming, such as cooling facilities, processing buildings, packaging facilities, and distribution centers. Gladstone Land pays monthly distributions to its stockholders and has paid 147 consecutive monthly cash distributions on its common stock since its initial public offering in January 2013. The current per-share distribution on its common stock is $0.0467 per month, or $0.5604 per year.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for LANDP 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