Starwood Property Trust Q4 adjusted profit slightly beats expectations on strong core business results

Starwood Property Trust (Maryland)

25/02/2026 12:09

Overview

Real estate finance firm's Q4 adjusted net income slightly beat analyst expectations

Company invested $2.5 bln in Q4, totaling $12.7 bln for the year

Company executed record $4.4 bln of capital transactions in 2025

Outlook

Starwood Property Trust plans to deploy cash across business lines to raise future earnings

Company expects long-term accretive impact from Fundamental net lease business acquisition

Starwood Property Trust highlights strong access to capital markets for future growth

Result Drivers

CORE BUSINESS PERFORMANCE - Strong results in global commercial and infrastructure lending contributed to quarterly performance

FUNDAMENTAL NET LEASE ACQUISITION - Acquisition expected to be accretive long-term due to reliable cash flows and rent increases

SECURITIZATION AND REFINANCING - Increased securitization pace and refinancing led to higher cash levels for strategic deployment

Company press release: ID:nPn3ydxbBa

Key Details

Metric
Beat/Miss
Actual
Consensus Estimate
Q4 EPS
$0.26
Q4 Adjusted Net Income
Slight Beat*
$159.50 mln
$158.26 mln (6 Analysts)
Q4 Net Income
$96.90 mln


*Applies to a deviation of less than 1%; not applicable for per-share numbers.

Analyst Coverage

The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 6 "strong buy" or "buy", 3 "hold" and no "sell" or "strong sell"

The average consensus recommendation for the specialized reits peer group is "buy"

Wall Street's median 12-month price target for Starwood Property Trust Inc is $20.50, about 16% above its February 24 closing price of $17.68

The stock recently traded at 10 times the next 12-month earnings vs. a P/E of 10 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.)