O Reilly Automotive (ORLY) Tax Provisions (2009 - 2026)
O Reilly Automotive (ORLY) reported Tax Provisions of $236.51 million for Q3 2026, up 19.6% from $197.75 million a year earlier and up 13.2% from the prior quarter.
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Analysis
O Reilly Automotive (ORLY) Tax Provisions (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, O Reilly Automotive's Tax Provisions came in at $786.91 million, up 17.4% year-over-year; for FY2025, it was $701.96 million, up 6.6% from FY2024.
- Tax Provisions has a five-year compound annual growth rate of 6.4% (FY2020 to FY2025).
- By year, Tax Provisions came in at $658.38 million in FY2024 (unchanged), $658.17 million in FY2023 (+5.1%), $626.01 million in FY2022 (+1.4%) and $617.23 million in FY2021 (+20.1%).
- The Q3 2026 figure ranks as the highest quarterly Tax Provisions in data going back to Q1 2009.
- Year over year, Tax Provisions has now increased in each of the last six quarters, with growth averaging 11.3% over the last eight quarters.
- The high point for year-over-year Tax Provisions in five years was Q4 2025 (growth of 23.4%); the low point was Q3 2024 (a decline of 7.3%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $209.01 million (Q2 2026), $175.91 million (Q1 2026) and $165.48 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,931.82 Bn | 2,428.49 Bn | 107.37 Bn | 6.18 Bn |
| 2 | Home Depot | 348.68 Bn | 341.92 Bn | 16.12 Bn | 1.55 Bn |
| 3 | Tjx Companies | 150.97 Bn | 128.51 Bn | 5.07 Bn | 498.00 Mn |
| 4 | Lowes Companies | 128.03 Bn | 120.99 Bn | 8.58 Bn | 776.00 Mn |
| 5 | Ross Stores | 74.86 Bn | 57.79 Bn | 2.12 Bn | 283.46 Mn |
| 6 | O Reilly Automotive | 73.48 Bn | 72.56 Bn | 2.52 Bn | 209.01 Mn |
| 7 | Target | 72.25 Bn | 66.84 Bn | 8.94 Bn | 582.00 Mn |
| 8 | Carvana | 53.50 Bn | 43.09 Bn | 1.52 Bn | 69.00 Mn |
| 9 | Autozone | 53.15 Bn | 52.00 Bn | 3.52 Bn | 236.65 Mn |
| 10 | JD.com | 40.22 Bn | -80.66 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 209.01 Mn |
| Mar 31, 2026 | 175.91 Mn |
| Dec 31, 2025 | 165.48 Mn |
| Sep 30, 2025 | 197.75 Mn |
| Jun 30, 2025 | 192.86 Mn |
| Mar 31, 2025 | 145.87 Mn |
| Dec 31, 2024 | 134.07 Mn |
| Sep 30, 2024 | 182.46 Mn |
| Jun 30, 2024 | 188.71 Mn |
| Mar 31, 2024 | 153.15 Mn |
| Dec 31, 2023 | 119.03 Mn |
| Sep 30, 2023 | 196.84 Mn |
| Jun 30, 2023 | 181.77 Mn |
| Mar 31, 2023 | 160.54 Mn |
| Dec 31, 2022 | 117.68 Mn |
| Sep 30, 2022 | 176.41 Mn |
| Jun 30, 2022 | 180.54 Mn |
| Mar 31, 2022 | 151.38 Mn |
| Dec 31, 2021 | 125.25 Mn |
| Sep 30, 2021 | 161.88 Mn |
API Access
O Reilly Automotive Tax Provisions 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=tax-provisions&ticker=ORLY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "ticker": "ORLY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=tax-provisions&ticker=ORLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();