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AMERICAN TOWER CORP /MA/: share-based compensation expense

Share-based compensation expense for AMERICAN TOWER CORP /MA/. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All AMERICAN TOWER CORP /MA/ financial histories

What this measure means

Reported noncash expense for share-based payment arrangements. Noncash treatment does not mean the awards have no economic cost to shareholders.

Exact concept: us-gaap:ShareBasedCompensation. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2007-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Share-based compensation expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31174,200,000USD2026-02-2410-K · 0001053507-26-000035
2024-01-012024-12-31203,600,000USD2026-02-2410-K · 0001053507-26-000035
2023-01-012023-12-31195,700,000USD2026-02-2410-K · 0001053507-26-000035
2022-01-012022-12-31169,300,000USD2025-02-2510-K · 0001053507-25-000025
2021-01-012021-12-31119,500,000USD2024-02-2710-K · 0001053507-24-000011
2020-01-012020-12-31120,800,000USD2023-02-2310-K · 0001053507-23-000023
2019-01-012019-12-31111,400,000USD2022-02-2510-K · 0001053507-22-000017
2018-01-012018-12-31137,500,000USD2021-02-2510-K · 0001053507-21-000026
2017-01-012017-12-31108,500,000USD2020-02-2510-K · 0001053507-20-000028
2016-01-012016-12-3189,900,000USD2019-02-2710-K · 0001053507-19-000012
2015-01-012015-12-3190,500,000USD2018-02-2810-K · 0001053507-18-000006
2014-01-012014-12-3180,153,000USD2017-02-2710-K · 0001053507-17-000009
2013-01-012013-12-3168,138,000USD2016-02-2610-K · 0001053507-16-000018
2012-01-012012-12-3151,983,000USD2015-02-2410-K · 0001193125-15-059026
2011-01-012011-12-3147,437,000USD2014-02-2610-K · 0001193125-14-068001
2010-01-012010-12-3152,555,000USD2013-02-2710-K · 0001193125-13-077821
2009-01-012009-12-3160,670,000USD2012-02-2910-K · 0001193125-12-086162
2008-01-012008-12-3154,807,000USD2011-02-2810-K · 0001193125-11-050129
2007-01-012007-12-3154,603,000USD2010-03-0110-K · 0001193125-10-044876

Related financial histories

Inspect the source

Entity
AMERICAN TOWER CORP /MA/ / CIK 0001053507
Captured
2026-09-20T05:17:34.771Z
SEC response SHA-256
274a2cf2d92541f010690a4e13c29703d3b979fb0cc40e683f6236b218ab6048

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001053507.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))