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NUCOR CORP: diluted earnings per share

Diluted earnings per share for NUCOR CORP. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All NUCOR CORP financial histories

What this measure means

Reported earnings or loss per share under dilution rules. Antidilutive instruments may be excluded. A diluted value can equal the basic value without implying no potential dilution.

Exact concept: us-gaap:EarningsPerShareDiluted. 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 2026-09-19.

Selected filing history

Diluted earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-317.52USD/shares2026-02-2510-K · 0001193125-26-071575
2024-01-012024-12-318.46USD/shares2026-02-2510-K · 0001193125-26-071575
2023-01-012023-12-3118USD/shares2026-02-2510-K · 0001193125-26-071575
2022-01-012022-12-3128.79USD/shares2025-02-2710-K · 0000950170-25-028427
2021-01-012021-12-3123.16USD/shares2024-02-2710-K · 0000950170-24-021195
2020-01-012020-12-312.36USD/shares2023-03-0110-K · 0001564590-23-002793
2019-01-012019-12-314.14USD/shares2022-02-2810-K · 0001564590-22-007679
2018-01-012018-12-317.42USD/shares2021-02-2610-K · 0001564590-21-009503
2017-01-012017-12-314.1USD/shares2020-02-2810-K · 0001564590-20-007794
2016-01-012016-12-312.48USD/shares2019-02-2810-K · 0001193125-19-057744
2015-01-012015-12-310.25USD/shares2018-02-2810-K · 0001193125-18-064018
2014-01-012014-12-312.11USD/shares2017-02-2810-K · 0001193125-17-062124
2013-01-012013-12-311.52USD/shares2016-02-2610-K · 0001193125-16-481119
2012-01-012012-12-311.58USD/shares2015-02-2710-K · 0001193125-15-068895
2011-01-012011-12-312.45USD/shares2014-02-2810-K · 0001193125-14-077349
2010-01-012010-12-310.42USD/shares2013-02-2810-K · 0001193125-13-084517
2009-01-012009-12-31-0.94USD/shares2012-02-2810-K · 0001193125-12-083972
2008-01-012008-12-315.98USD/shares2011-02-2810-K · 0001193125-11-049351
2007-01-012007-12-314.94USD/shares2010-02-2510-K · 0001193125-10-040686

Related financial histories

Inspect the source

Entity
NUCOR CORP / CIK 0000073309
Captured
2026-09-19T14:50:37.636Z
SEC response SHA-256
9265f148393edf83f2797761e24c52bc061277a636d7df476b888ffaf6c74f3a

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/0000073309.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"])))