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Steel Dynamics, Inc.: share-based compensation expense

Share-based compensation expense for Steel Dynamics, Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Steel Dynamics, Inc. 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
2025-01-012025-12-3168,983,000USD2026-02-2710-K · 0001104659-26-021395
2024-01-012024-12-3166,589,000USD2026-02-2710-K · 0001104659-26-021395
2023-01-012023-12-3161,744,000USD2026-02-2710-K · 0001104659-26-021395
2022-01-012022-12-3159,240,000USD2025-02-2810-K · 0001558370-25-001886
2021-01-012021-12-3157,715,000USD2024-02-2910-K · 0001558370-24-002152
2020-01-012020-12-3155,598,000USD2023-02-2810-K · 0001558370-23-002303
2019-01-012019-12-3147,631,000USD2022-02-2810-K · 0001558370-22-002377
2018-01-012018-12-3143,317,000USD2021-03-0110-K · 0001558370-21-002129
2017-01-012017-12-3136,197,000USD2020-02-2710-K · 0001558370-20-001641
2016-01-012016-12-3131,656,000USD2019-02-2710-K · 0001144204-19-010579
2015-01-012015-12-3130,181,000USD2018-02-2710-K · 0001144204-18-011155
2014-01-012014-12-3124,035,000USD2017-02-2810-K · 0001144204-17-011732
2013-01-012013-12-3115,504,000USD2016-02-2610-K · 0001047469-16-010496
2012-01-012012-12-3112,481,000USD2015-03-0210-K · 0001047469-15-001486
2011-01-012011-12-3117,283,000USD2014-03-0310-K · 0001047469-14-001662
2010-01-012010-12-3114,688,000USD2013-02-2710-K · 0001047469-13-001827
2009-01-012009-12-3117,589,000USD2012-02-2710-K · 0001047469-12-001586
2008-01-012008-12-3114,278,000USD2011-02-2310-K · 0001047469-11-001181
2007-01-012007-12-318,073,000USD2010-02-2210-K · 0001047469-10-001104

Related financial histories

Inspect the source

Entity
Steel Dynamics, Inc. / CIK 0001022671
Captured
2026-09-20T05:13:42.986Z
SEC response SHA-256
05faeb3700549a72e77fc8cdb107ba5bc36b73512de61c7a9a9c0e305a5d5943

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/0001022671.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"])))