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AUTOZONE INC: basic weighted-average shares

Basic weighted-average shares for AUTOZONE INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All AUTOZONE INC financial histories

What this measure means

Time-weighted shares used for basic earnings per share. This denominator differs from shares outstanding at a single reporting date.

Exact concept: us-gaap:WeightedAverageNumberOfSharesOutstandingBasic. 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 2007-08-26 to 2025-08-30. The SEC response was captured on 2026-09-20.

Selected filing history

Basic weighted-average shares in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2024-09-012025-08-3016,789,000shares2025-10-2710-K · 0001104659-25-102611
2023-08-272024-08-3117,309,000shares2025-10-2710-K · 0001104659-25-102611
2022-08-282023-08-2618,510,000shares2025-10-2710-K · 0001104659-25-102611
2021-08-292022-08-2720,107,000shares2024-10-2810-K · 0001558370-24-013758
2020-08-302021-08-2822,237,000shares2023-10-2410-K · 0001558370-23-016668
2019-09-012020-08-2923,540,000shares2022-10-2410-K · 0001558370-22-015239
2018-08-262019-08-3124,966,000shares2021-10-2510-K · 0001558370-21-013446
2017-08-272018-08-2526,970,000shares2020-10-2610-K · 0001558370-20-011748
2016-08-282017-08-2628,430,000shares2019-10-2810-K · 0001193125-19-276201
2015-08-302016-08-2729,889,000shares2018-10-2410-K · 0001193125-18-306452
2014-08-312015-08-2931,560,000shares2017-10-2510-K · 0001193125-17-319357
2013-09-012014-08-3033,267,000shares2016-10-2410-K · 0001193125-16-745160
2012-08-262013-08-3135,943,000shares2015-10-2610-K · 0001193125-15-353476
2011-08-282012-08-2538,696,000shares2014-10-2710-K · 0001193125-14-383401
2010-08-292011-08-2742,632,000shares2013-10-2810-K · 0001193125-13-413428
2009-08-302010-08-2848,488,000shares2012-10-2210-K · 0001193125-12-430271
2008-08-312009-08-2955,282,000shares2011-10-2410-K · 0000950123-11-091540
2007-08-262008-08-3063,295,000shares2010-10-2510-K · 0000950123-10-095687

Related financial histories

Inspect the source

Entity
AUTOZONE INC / CIK 0000866787
Captured
2026-09-20T05:00:12.814Z
SEC response SHA-256
0e652965cdc4fd7aa88190116e50474ffbf31ea6b4451b50b3b784af0eadc4d6

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/0000866787.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"])))