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FRT Federal Realty Investment Trust News Story

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FinancialsConservativeLarge CapNeutral

Federal Realty Q1 FFO per share rises on record leasing, raises 2026 view

Overview

US retail property REIT's Q1 rental income and FFO per share rose over prior year

Company reported record leasing activity and 4.7% comparable property income growth

Company raised 2026 earnings and FFO per share guidance

Outlook

Federal Realty raises 2026 earnings per diluted share guidance to $3.94-$4.03 from $3.90-$4.00

Company lifts 2026 Nareit FFO and Core FFO per diluted share guidance to $7.46-$7.55

Federal Realty expects 2026 Core FFO growth of 5.7%-6.9% over prior year

Result Drivers

RECORD LEASING ACTIVITY - Co signed a first-quarter record 101 leases for 649,078 sq ft of comparable retail space, driving rent growth of 13% on a cash basis and 23% on a straight-line basis

COMPARABLE PROPERTY INCOME GROWTH - Comparable property operating income rose 4.7%, with adjusted growth of 5.1%

HIGH OCCUPANCY - Portfolio occupancy was 93.8% and leased rate 96.1% at quarter end, with year-over-year increases

Company press release: ID:nPn9HZkY3a

Key Details

MetricBeat/MissActualConsensus Estimate
Q1 Rental Income$332.66 mln
Q1 EPS$1.81
Q1 Net Income available for common shareholders$157.09 mln
Q1 FFO$162.60 mln
Q1 FFO Per Share$1.88
Q1 Operating Income$208.99 mln
Analyst Coverage The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 11 "strong buy" or "buy", 9 "hold" and no "sell" or "strong sell" The average consensus recommendation for the commercial reits peer group is "buy" Wall Street's median 12-month price target for Federal Realty Investment Trust is $116.00, about 4.6% above its April 30 closing price of $110.90 The stock recently traded at 37 times the next 12-month earnings vs. a P/E of 33 three months ago For questions concerning the data in this report, contact Estimates.Support@lseg.com. For any other questions or feedback, contact reuters.support@thomsonreuters.com. (This story was created using Reuters automation and AI based on LSEG and company data. It was checked and edited by a Reuters journalist prior to publication.)

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