O Reilly Automotive (ORLY) Operating Expenses (2009 - 2026)
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Analysis
O Reilly Automotive (ORLY) Operating Expenses (2009 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,931.82 Bn | 2,428.49 Bn | 107.37 Bn | 173.87 Bn |
| 2 | Home Depot | 348.68 Bn | 341.92 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 150.97 Bn | 128.51 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 128.03 Bn | 120.99 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.86 Bn | 57.79 Bn | 2.12 Bn | 1.02 Bn |
| 6 | O Reilly Automotive | 73.48 Bn | 72.56 Bn | 2.52 Bn | 1.53 Bn |
| 7 | Target | 72.25 Bn | 66.84 Bn | 8.94 Bn | 5.73 Bn |
| 8 | Carvana | 53.50 Bn | 43.09 Bn | 1.52 Bn | 805.00 Mn |
| 9 | Autozone | 53.15 Bn | 52.00 Bn | 3.52 Bn | 2.20 Bn |
| 10 | JD.com | 40.22 Bn | -80.66 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.53 Bn |
| Mar 31, 2026 | 1.51 Bn |
| Dec 31, 2025 | 1.46 Bn |
| Sep 30, 2025 | 1.46 Bn |
| Jun 30, 2025 | 1.41 Bn |
| Mar 31, 2025 | 1.38 Bn |
| Dec 31, 2024 | 1.36 Bn |
| Sep 30, 2024 | 1.35 Bn |
| Jun 30, 2024 | 1.30 Bn |
| Mar 31, 2024 | 1.28 Bn |
| Dec 31, 2023 | 1.25 Bn |
| Sep 30, 2023 | 1.26 Bn |
| Jun 30, 2023 | 1.23 Bn |
| Mar 31, 2023 | 1.17 Bn |
| Dec 31, 2022 | 1.17 Bn |
| Sep 30, 2022 | 1.13 Bn |
| Jun 30, 2022 | 1.09 Bn |
| Mar 31, 2022 | 1.04 Bn |
| Dec 31, 2021 | 1.06 Bn |
| Sep 30, 2021 | 1.06 Bn |
API Access
O Reilly Automotive Operating 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=operating-expenses&ticker=ORLY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-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=operating-expenses&ticker=ORLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();