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Grand Canyon Education Q2 adjusted EBITDA beats expectations, revenue up 8.8%
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Grand Canyon Education Q2 adjusted EBITDA beats expectations, revenue up 8.8%
Aug 6, 2025 1:39 PM

Overview

* Grand Canyon Education ( LOPE ) Q2 service revenue rises 8.8% yr/yr, driven by enrollment growth

* Adjusted EBITDA beats analyst expectations, reflecting strong operational performance, per LSEG data

* Net income for Q2 increases 19.1%, reflecting improved profitability

Outlook

* Grand Canyon Education ( LOPE ) sees Q3 service revenue between $258.5 mln and $260.5 mln

* Company expects Q4 operating margin between 35.1% and 35.8%

* Grand Canyon Education ( LOPE ) projects full-year diluted EPS between $8.75 and $8.90

* Company anticipates Q3 diluted EPS of between$1.69and$1.74

Result Drivers

* ENROLLMENT GROWTH - Service revenue increase driven by 10.3% rise in partner enrollments

* CONTRACT MODIFICATIONS - Revenue per student decreased due to reduced revenue share percentage and shift to lower tuition rate students

* ABSN STUDENTS - Higher revenue per student from accelerated Bachelor of Science in Nursing (ABSN) students at off-campus sites with higher tuition rates

Key Details

Metric Beat/Mis Actual Consensu

s s

Estimate

Q2 Net $41.55

Income mln

Q2 Beat $67.40 $60.70

Adjusted mln mln (2

EBITDA Analysts

)

Q2 Beat $55.02 $50.80

Pretax mln mln (2

Profit Analysts

)

Q2 $51.79

Operatin mln

g Income

Q2 $247.50

Service mln

revenue

Analyst Coverage

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

* The average consensus recommendation for the miscellaneous educational service providers peer group is "buy."

* Wall Street's median 12-month price target for Grand Canyon Education Inc ( LOPE ) is $215.00, about 22% above its August 5 closing price of $167.66

* The stock recently traded at 18 times the next 12-month earnings vs. a P/E of 20 three months ago

Press Release:

(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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