Lamar Advertising (LAMR) Operating Expenses (2009 - 2026)
Lamar Advertising's Operating Expenses was $408.79 million in Q2 2026, up 7.1% from $381.63 million a year earlier and up 7.0% from the prior quarter.
Lamar Advertising (LAMR) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Lamar Advertising's Operating Expenses was $1.59 billion through Jun 30, 2026, down 1.8% year-over-year; for FY2025, it was $1.49 billion, down 10.9% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 5.2% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.68 billion in FY2024 (+16.7%), $1.44 billion in FY2023 (-1.3%), $1.45 billion in FY2022 (+14.8%) and $1.27 billion in FY2021 (+9.3%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q4 2024.
- Compared with a year earlier, Operating Expenses was higher in six of the last eight quarters, with growth averaging 5.9%.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2024 (growth of 49.1%); the worst was Q4 2025 (a decline of 26.3%).
- Per Business Quant data, LAMR's Operating Expenses in the three quarters before Q2 2026 was $381.94 million (Q1 2026), $399.87 million (Q4 2025) and $396.46 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | American Tower | 78.00 Bn | 77.74 Bn | 2.72 Bn | 1.48 Bn |
| 2 | Digital Realty Trust | 65.33 Bn | 55.85 Bn | - | 1.46 Bn |
| 3 | Crown Castle | 28.57 Bn | 27.31 Bn | 989.00 Mn | 538.00 Mn |
| 4 | Sba Communications | 17.27 Bn | 17.36 Bn | 539.27 Mn | 363.41 Mn |
| 5 | Lamar Advertising | 12.72 Bn | 12.54 Bn | 422.53 Mn | 408.79 Mn |
| 6 | OUTFRONT Media | 4.93 Bn | 4.69 Bn | 276.40 Mn | 406.40 Mn |
| 7 | Array Digital Infrastructure | 2.93 Bn | 1.83 Bn | 30.57 Mn | -345.19 Mn |
| 8 | IHS Holding | 2.81 Bn | -54.39 Mn | 207.10 Mn | -125.40 Mn |
| 9 | Fermi | 2.73 Bn | 1.87 Bn | - | 26.76 Mn |
| 10 | Clear Channel Outdoor Holdings | 1.19 Bn | 478.09 Mn | 241.86 Mn | 69.97 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 408.79 Mn |
| Mar 31, 2026 | 381.94 Mn |
| Dec 31, 2025 | 399.87 Mn |
| Sep 30, 2025 | 396.46 Mn |
| Jun 30, 2025 | 381.63 Mn |
| Mar 31, 2025 | 314.20 Mn |
| Dec 31, 2024 | 542.91 Mn |
| Sep 30, 2024 | 377.58 Mn |
| Jun 30, 2024 | 381.02 Mn |
| Mar 31, 2024 | 373.55 Mn |
| Dec 31, 2023 | 364.20 Mn |
| Sep 30, 2023 | 354.48 Mn |
| Jun 30, 2023 | 364.35 Mn |
| Mar 31, 2023 | 352.53 Mn |
| Dec 31, 2022 | 425.46 Mn |
| Sep 30, 2022 | 346.40 Mn |
| Jun 30, 2022 | 351.35 Mn |
| Mar 31, 2022 | 330.93 Mn |
| Dec 31, 2021 | 344.63 Mn |
| Sep 30, 2021 | 343.56 Mn |
Lamar Advertising Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=LAMR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LAMR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=LAMR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();