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JAMES HARDIE INDUSTRIES plc: share-based compensation expense

Share-based compensation expense for JAMES HARDIE INDUSTRIES plc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All JAMES HARDIE INDUSTRIES plc 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 2008-04-01 to 2026-03-31. 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
2025-04-012026-03-3138,000,000USD2026-05-1910-K · 0001159152-26-000045
2024-04-012025-03-3123,000,000USD2026-05-1910-K · 0001159152-26-000045
2023-04-012024-03-3128,200,000USD2026-05-1910-K · 0001159152-26-000045
2022-04-012023-03-3115,700,000USD2025-05-2020-F · 0001159152-25-000012
2021-04-012022-03-319,000,000USD2024-05-2020-F · 0001159152-24-000016
2020-04-012021-03-3118,000,000USD2023-05-1620-F · 0001159152-23-000015
2019-04-012020-03-3110,300,000USD2022-05-1720-F · 0001159152-22-000026
2018-04-012019-03-3112,500,000USD2021-05-1820-F · 0001159152-21-000045
2017-04-012018-03-3111,100,000USD2020-05-1920-F · 0001159152-20-000036
2016-04-012017-03-319,300,000USD2019-05-2120-F · 0001159152-19-000045
2015-04-012016-03-3110,300,000USD2018-05-2220-F · 0001159152-18-000030
2014-04-012015-03-319,200,000USD2017-05-1820-F · 0001193125-17-174339
2013-04-012014-03-318,500,000USD2016-05-1920-F · 0001193125-16-595132
2012-04-012013-03-317,000,000USD2015-05-2120-F · 0001193125-15-195809
2011-04-012012-03-317,800,000USD2014-06-2620-F · 0001193125-14-251077
2010-04-012011-03-319,100,000USD2013-06-2720-F · 0001193125-13-274942
2009-04-012010-03-317,700,000USD2012-07-0220-F · 0001193125-12-292232
2008-04-012009-03-317,200,000USD2011-06-2920-F · 0000950123-11-062797

Related financial histories

Inspect the source

Entity
JAMES HARDIE INDUSTRIES plc / CIK 0001159152
Captured
2026-09-20T07:42:58.930Z
SEC response SHA-256
c26233c655cb2b6e6b9cde50f6cc56ca53e54cb270e1072fb860db41bc76f765

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/0001159152.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"])))