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Asset logo for symbol FRT
Federal Realty Investment Trust
Asset logo for symbol FRT



AI Deep-Learning Forecast (FRT)

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Federal Realty Investment Trust (FRT) Stocklytics Forecast

According to our analysis, Federal Realty Investment Trust (FRT) has a positive forecast for its stock price in the coming years. Based on historical data and market trends, we predict that FRT's stock price will continue to rise steadily over the next few years. This prediction is supported by the company's strong financial performance and solid growth prospects.

In particular, FRT has a strong track record of generating consistent revenue and earnings growth. The trust's focus on owning and operating high-quality retail properties in prime locations has allowed it to attract premium tenants and achieve high occupancy rates. Additionally, FRT has a diversified portfolio that includes various types of properties, such as shopping centers, mixed-use developments, and urban retail destinations. This diversification further strengthens its stability and growth potential.

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Frequently Asked Questions

What is the analyst price prediction for Federal Realty Investment Trust (FRT) stock?

Analysts have set a target price of $109.48 for Federal Realty Investment Trust (FRT), based on forecasts from 23 analysts. The predicted price range extends from a high of $124 to a low of $95. This represents a potential increase of up to 16.57% and a decrease of -10.69% from the current price of $106.37. These forecasts are as of 2023 May 26.

What are the analyst ratings for Federal Realty Investment Trust (FRT) stock?

Currently, there are no analyst ratings available for Federal Realty Investment Trust (FRT), possibly due to insufficient coverage or recent updates.

What is the AI price prediction for Federal Realty Investment Trust (FRT) stock?

At present, there is no AI or machine-learning-based price prediction available for Federal Realty Investment Trust (FRT) stock. The lack of a forecast could stem from various factors, such as inadequate data or the necessity for model recalibration.


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