American Tower Corp /Ma/ (AMT) Property Operating Expenses (2009 - 2026)
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Analysis
American Tower Corp /Ma/ (AMT) Property Operating Expenses (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
Historic Data
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Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 707.90 Mn |
| Mar 31, 2026 | 664.80 Mn |
| Dec 31, 2025 | 676.90 Mn |
| Sep 30, 2025 | 657.00 Mn |
| Jun 30, 2025 | 640.60 Mn |
| Mar 31, 2025 | 599.60 Mn |
| Dec 31, 2024 | 622.60 Mn |
| Sep 30, 2024 | 626.90 Mn |
| Jun 30, 2024 | 627.30 Mn |
| Mar 31, 2024 | 605.00 Mn |
| Dec 31, 2023 | 624.40 Mn |
| Sep 30, 2023 | 625.50 Mn |
| Jun 30, 2023 | 810.10 Mn |
| Mar 31, 2023 | 787.00 Mn |
| Dec 31, 2022 | 87.50 Mn |
| Sep 30, 2022 | 808.80 Mn |
| Jun 30, 2022 | 794.00 Mn |
| Mar 31, 2022 | 771.50 Mn |
| Dec 31, 2021 | 705.30 Mn |
| Sep 30, 2021 | 693.40 Mn |
API Access
American Tower Corp /Ma/ Property 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=property-operating-expenses&ticker=AMT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-operating-expenses", "ticker": "AMT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=property-operating-expenses&ticker=AMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();