Lamar Advertising (LAMR) Accumulated Expenses (2009 - 2026)
Lamar Advertising (LAMR) posted Accumulated Expenses of $122.15 million for Q2 2026, up 8.8% from $112.28 million a year earlier and up 7.9% from the prior quarter.
Lamar Advertising (LAMR) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Lamar Advertising's Accumulated Expenses came in at $138.68 million, up 3.5% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 5.7% (FY2020 to FY2025).
- In prior years, Lamar Advertising's Accumulated Expenses was $133.94 million in FY2024 (+25.0%), $107.2 million in FY2023 (-8.8%), $117.59 million in FY2022 (-12.9%) and $135.04 million in FY2021 (+28.3%).
- Quarterly Accumulated Expenses has run from a low of $79.48 million in Q1 2024 to a high of $138.68 million in Q4 2025 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last nine quarters, with growth averaging 15.4% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q3 2021, with growth of 48.9%; the weakest was Q4 2022, with a decline of 12.9%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $113.21 million (Q1 2026), $138.68 million (Q4 2025) and $123.38 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | American Tower | 76.26 Bn | 75.99 Bn | 2.72 Bn |
| 2 | Digital Realty Trust | 64.98 Bn | 55.50 Bn | - |
| 3 | Crown Castle | 28.39 Bn | 27.14 Bn | 989.00 Mn |
| 4 | Sba Communications | 16.99 Bn | 17.07 Bn | 539.27 Mn |
| 5 | Lamar Advertising | 12.56 Bn | 12.38 Bn | 422.53 Mn |
| 6 | OUTFRONT Media | 4.89 Bn | 4.65 Bn | 276.40 Mn |
| 7 | Array Digital Infrastructure | 2.92 Bn | 1.81 Bn | 30.57 Mn |
| 8 | IHS Holding | 2.80 Bn | -57.74 Mn | 207.10 Mn |
| 9 | Fermi | 2.69 Bn | 1.82 Bn | - |
| 10 | Clear Channel Outdoor Holdings | 1.20 Bn | 488.27 Mn | 241.86 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 122.15 Mn |
| Mar 31, 2026 | 113.21 Mn |
| Dec 31, 2025 | 138.68 Mn |
| Sep 30, 2025 | 123.38 Mn |
| Jun 30, 2025 | 112.28 Mn |
| Mar 31, 2025 | 111.55 Mn |
| Dec 31, 2024 | 133.94 Mn |
| Sep 30, 2024 | 110.63 Mn |
| Jun 30, 2024 | 95.60 Mn |
| Mar 31, 2024 | 79.48 Mn |
| Dec 31, 2023 | 107.20 Mn |
| Sep 30, 2023 | 96.29 Mn |
| Jun 30, 2023 | 87.50 Mn |
| Mar 31, 2023 | 82.72 Mn |
| Dec 31, 2022 | 117.59 Mn |
| Sep 30, 2022 | 105.37 Mn |
| Jun 30, 2022 | 99.22 Mn |
| Mar 31, 2022 | 84.87 Mn |
| Dec 31, 2021 | 135.04 Mn |
| Sep 30, 2021 | 114.19 Mn |
Lamar Advertising Accumulated 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=accumulated-expenses&ticker=LAMR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=LAMR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();