O Reilly Automotive (ORLY) Other Accumulated Expenses (2009 - 2026)
O Reilly Automotive (ORLY) posted Other Accumulated Expenses of $1.07 billion for Q2 2026, up 87.0% from $573.08 million a year earlier and up 33.2% from the prior quarter.
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Analysis
O Reilly Automotive (ORLY) Other Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, O Reilly Automotive's Other Accumulated Expenses came in at $561.29 million, down 36.0% from FY2024.
- Annual Other Accumulated Expenses shows a five-year compound annual growth rate of 13.5% (FY2020 to FY2025).
- In prior years, O Reilly Automotive's Other Accumulated Expenses was $876.73 million in FY2024 (+19.9%), $730.94 million in FY2023 (+90.5%), $383.69 million in FY2022 (+3.6%) and $370.22 million in FY2021 (+24.5%).
- The Q2 2026 figure stands as the highest quarterly Other Accumulated Expenses in data going back to Q4 2009.
- On a year-over-year basis, Other Accumulated Expenses increased in four of the last eight quarters, with growth averaging 8.3%.
- The strongest year-over-year quarter for Other Accumulated Expenses in the past five years was Q2 2024, with growth of 111.1%; the weakest was Q2 2025, with a decline of 39.7%.
- According to Business Quant data, Other Accumulated Expenses for the three prior quarters was $804.46 million (Q1 2026), $561.29 million (Q4 2025) and $610.52 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Amazon Com | 2,712.14 Bn | 2,228.84 Bn | 104.83 Bn |
| 2 | Home Depot | 282.27 Bn | 275.52 Bn | 16.12 Bn |
| 3 | Tjx Companies | 146.16 Bn | 123.70 Bn | 5.07 Bn |
| 4 | Lowes Companies | 101.42 Bn | 94.39 Bn | 8.58 Bn |
| 5 | Ross Stores | 73.06 Bn | 55.98 Bn | 2.12 Bn |
| 6 | Target | 70.86 Bn | 65.45 Bn | 8.94 Bn |
| 7 | Carvana | 70.11 Bn | 61.71 Bn | 1.38 Bn |
| 8 | O Reilly Automotive | 69.29 Bn | 68.38 Bn | 2.52 Bn |
| 9 | Autozone | 45.61 Bn | 44.51 Bn | 2.52 Bn |
| 10 | JD.com | 31.28 Bn | -78.90 Bn | 8.71 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.07 Bn |
| Mar 31, 2026 | 804.46 Mn |
| Dec 31, 2025 | 561.29 Mn |
| Sep 30, 2025 | 610.52 Mn |
| Jun 30, 2025 | 573.08 Mn |
| Mar 31, 2025 | 910.98 Mn |
| Dec 31, 2024 | 876.73 Mn |
| Sep 30, 2024 | 743.98 Mn |
| Jun 30, 2024 | 950.15 Mn |
| Mar 31, 2024 | 791.63 Mn |
| Dec 31, 2023 | 730.94 Mn |
| Sep 30, 2023 | 496.15 Mn |
| Jun 30, 2023 | 450.17 Mn |
| Mar 31, 2023 | 427.01 Mn |
| Dec 31, 2022 | 383.69 Mn |
| Sep 30, 2022 | 424.00 Mn |
| Jun 30, 2022 | 417.79 Mn |
| Mar 31, 2022 | 393.76 Mn |
| Dec 31, 2021 | 370.22 Mn |
| Sep 30, 2021 | 385.98 Mn |
API Access
O Reilly Automotive Other Accumulated Expenses 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=other-accumulated-expenses&ticker=ORLY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "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=other-accumulated-expenses&ticker=ORLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();