American Tower Corp /Ma/ (AMT) Total Operating Expenses (2009 - 2026)
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Analysis
American Tower Corp /Ma/ (AMT) Total Operating Expenses (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.48 Bn |
| Mar 31, 2026 | 1.50 Bn |
| Dec 31, 2025 | 1.58 Bn |
| Sep 30, 2025 | 1.48 Bn |
| Jun 30, 2025 | 1.43 Bn |
| Mar 31, 2025 | 1.31 Bn |
| Dec 31, 2024 | 1.47 Bn |
| Sep 30, 2024 | 1.38 Bn |
| Jun 30, 2024 | 1.39 Bn |
| Mar 31, 2024 | 1.37 Bn |
| Dec 31, 2023 | 1.84 Bn |
| Sep 30, 2023 | 1.61 Bn |
| Jun 30, 2023 | 1.90 Bn |
| Mar 31, 2023 | 1.99 Bn |
| Dec 31, 2022 | 1.06 Bn |
| Sep 30, 2022 | 2.02 Bn |
| Jun 30, 2022 | 1.89 Bn |
| Mar 31, 2022 | 1.94 Bn |
| Dec 31, 2021 | 1.82 Bn |
| Sep 30, 2021 | 1.63 Bn |
API Access
American Tower Corp /Ma/ Total 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=total-operating-expenses&ticker=AMT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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=total-operating-expenses&ticker=AMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();