Autozone (AZO) Depreciation & Amortization (CF) (2009 - 2026)
Autozone's Depreciation & Amortization (CF) was $220.14 million in fiscal Q4 2026 (quarter ended Aug 29, 2026), up 11.5% from $197.41 million a year earlier.
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Analysis
Autozone (AZO) Depreciation & Amortization (CF) (2009 - 2026) Analysis & Trends
For FY2026 (ended Aug 29, 2026), Depreciation & Amortization (CF) at Autozone came in at $684.27 million, up 11.6% from FY2025.
- Depreciation & Amortization (CF) has now increased for 17 consecutive fiscal years, with a five-year compound annual growth rate of 10.9% (FY2021 to FY2026).
- In earlier fiscal years, Depreciation & Amortization (CF) was $613.2 million in FY2025 (+11.5%), $549.76 million in FY2024 (+10.5%), $497.58 million in FY2023 (+12.5%) and $442.22 million in FY2022 (+8.5%).
- The fiscal Q4 2026 figure marks the highest quarterly Depreciation & Amortization (CF) in data going back to fiscal Q3 2009.
- Compared with a year earlier, Depreciation & Amortization (CF) has increased for 23 straight quarters, with growth averaging 11.5% over the last eight quarters.
- Over the past five years, the year-over-year growth in Depreciation & Amortization (CF) ranged from 5.5% (fiscal Q2 2022) to 14.1% (fiscal Q2 2023).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Dep. & Amort. (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,979.57 Bn | 2,476.24 Bn | 107.37 Bn | 20.95 Bn |
| 2 | Home Depot | 350.34 Bn | 343.58 Bn | 16.12 Bn | 929.00 Mn |
| 3 | Tjx Companies | 150.76 Bn | 128.31 Bn | 5.07 Bn | 340.00 Mn |
| 4 | Lowes Companies | 130.11 Bn | 123.07 Bn | 8.58 Bn | 648.00 Mn |
| 5 | Carvana | 80.38 Bn | 71.27 Bn | 1.52 Bn | 64.00 Mn |
| 6 | Ross Stores | 76.38 Bn | 59.31 Bn | 2.12 Bn | 140.19 Mn |
| 7 | Target | 73.52 Bn | 68.11 Bn | 8.94 Bn | 784.00 Mn |
| 8 | O Reilly Automotive | 71.92 Bn | 71.02 Bn | 2.68 Bn | 139.55 Mn |
| 9 | Autozone | 52.04 Bn | 50.89 Bn | 3.52 Bn | 220.14 Mn |
| 10 | JD.com | 34.34 Bn | -76.55 Bn | 8.74 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 29, 2026 | 220.14 Mn |
| May 9, 2026 | 160.29 Mn |
| Feb 14, 2026 | 155.64 Mn |
| Nov 22, 2025 | 148.19 Mn |
| Aug 30, 2025 | 197.41 Mn |
| May 10, 2025 | 144.70 Mn |
| Feb 15, 2025 | 137.92 Mn |
| Nov 23, 2024 | 133.17 Mn |
| Aug 31, 2024 | 175.34 Mn |
| May 4, 2024 | 129.22 Mn |
| Feb 10, 2024 | 124.97 Mn |
| Nov 18, 2023 | 120.22 Mn |
| Aug 26, 2023 | 158.49 Mn |
| May 6, 2023 | 116.12 Mn |
| Feb 11, 2023 | 113.71 Mn |
| Nov 19, 2022 | 109.25 Mn |
| Aug 27, 2022 | 140.86 Mn |
| May 7, 2022 | 102.08 Mn |
| Feb 12, 2022 | 99.69 Mn |
| Nov 20, 2021 | 99.59 Mn |
API Access
Autozone Depreciation & Amortization (CF) 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=depreciation-and-amortization-cf&ticker=AZO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "depreciation-and-amortization-cf", "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=depreciation-and-amortization-cf&ticker=AZO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();