Autozone (AZO) Shares Outstanding (Diluted) (2009 - 2026)
Autozone's Weighted Average Shares Outstanding (Diluted) came in at 16.87 million for fiscal Q4 2026 (quarter ended Aug 29, 2026), down 2.2% from 17.25 million a year earlier.
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Analysis
Autozone (AZO) Shares Outstanding (Diluted) (2009 - 2026) Analysis & Trends
Going back to fiscal Q2 2009, Autozone's Weighted Average Shares Outstanding (Diluted) data covers 71 quarters.
- Weighted Average Shares Outstanding (Diluted) has declined in each of the last 17 fiscal years, with a five-year compound annual growth rate of -5.9% (FY2021 to FY2026).
- Going back by fiscal year, Weighted Average Shares Outstanding (Diluted) was 17.25 million in FY2025 (-3.1%), 17.8 million in FY2024 (-6.8%), 19.1 million in FY2023 (-7.9%) and 20.73 million in FY2022 (-9.1%).
- The five-year range for quarterly Weighted Average Shares Outstanding (Diluted) is 16.85 million (fiscal Q3 2026) to 21.61 million (fiscal Q1 2022).
- Year-over-year, Weighted Average Shares Outstanding (Diluted) has declined for 67 consecutive quarters, with an average decline of 2.7% over the last eight quarters.
- Across the past five years, year-over-year decline in Weighted Average Shares Outstanding (Diluted) ran from 1.5% in fiscal Q1 2026 to 9.3% in fiscal Q3 2022.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Shares Outstanding (Dil.) (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,933.26 Bn | 2,429.93 Bn | 107.37 Bn | 10.93 Bn |
| 2 | Home Depot | 348.06 Bn | 341.30 Bn | 16.12 Bn | 996.00 Mn |
| 3 | Tjx Companies | 147.97 Bn | 125.52 Bn | 5.07 Bn | 1.12 Bn |
| 4 | Lowes Companies | 127.73 Bn | 120.69 Bn | 8.58 Bn | 560.00 Mn |
| 5 | Carvana | 79.78 Bn | 70.66 Bn | 1.52 Bn | 739.91 Mn |
| 6 | O Reilly Automotive | 74.18 Bn | 73.27 Bn | 2.68 Bn | 812.20 Mn |
| 7 | Ross Stores | 74.06 Bn | 56.99 Bn | 2.12 Bn | 319.45 Mn |
| 8 | Target | 73.34 Bn | 67.93 Bn | 8.94 Bn | 456.60 Mn |
| 9 | Autozone | 52.71 Bn | 51.56 Bn | 3.52 Bn | 16.87 Mn |
| 10 | JD.com | 33.86 Bn | -77.03 Bn | 8.74 Bn | 1.49 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 29, 2026 | 16.87 Mn |
| May 9, 2026 | 16.85 Mn |
| Feb 14, 2026 | 16.97 Mn |
| Nov 22, 2025 | 17.10 Mn |
| Aug 30, 2025 | 17.25 Mn |
| May 10, 2025 | 17.21 Mn |
| Feb 15, 2025 | 17.25 Mn |
| Nov 23, 2024 | 17.37 Mn |
| Aug 31, 2024 | 17.80 Mn |
| May 4, 2024 | 17.76 Mn |
| Feb 10, 2024 | 17.83 Mn |
| Nov 18, 2023 | 18.23 Mn |
| Aug 26, 2023 | 19.10 Mn |
| May 6, 2023 | 18.98 Mn |
| Feb 11, 2023 | 19.34 Mn |
| Nov 19, 2022 | 19.65 Mn |
| Aug 27, 2022 | 20.73 Mn |
| May 7, 2022 | 20.41 Mn |
| Feb 12, 2022 | 21.16 Mn |
| Nov 20, 2021 | 21.61 Mn |
API Access
Autozone Shares Outstanding (Diluted) API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=shares-outstanding-diluted&ticker=AZO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "shares-outstanding-diluted", "ticker": "AZO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=shares-outstanding-diluted&ticker=AZO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();