O Reilly Automotive (ORLY) Interest Expenses (2009 - 2026)
O Reilly Automotive (ORLY) reported Interest Expenses of $69.87 million for Q2 2026, up 21.9% from $57.34 million a year earlier and up 11.4% from the prior quarter.
O Reilly Automotive (ORLY) Interest Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, O Reilly Automotive's Interest Expenses came in at $252.78 million, up 12.1% year-over-year; for FY2025, it came in at $235.06 million, up 5.6% from FY2024.
- Interest Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 7.8% (FY2020 to FY2025).
- By year, Interest Expenses came in at $222.55 million in FY2024 (+10.4%), $201.67 million in FY2023 (+27.9%), $157.72 million in FY2022 (+8.9%) and $144.77 million in FY2021 (-10.2%).
- The Q2 2026 figure ranks as the highest quarterly Interest Expenses in data going back to Q1 2009.
- Year over year, Interest Expenses has now increased in each of the last six quarters, with growth averaging 7.4% over the last eight quarters.
- The high point for year-over-year Interest Expenses in five years was Q2 2023 (growth of 32.6%); the low point was Q3 2021 (a decline of 16.3%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $62.75 million (Q1 2026), $60.6 million (Q4 2025) and $59.57 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Int Expense (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,816.63 Bn | 2,333.33 Bn | 104.83 Bn | 1.31 Bn |
| 2 | Home Depot | 311.72 Bn | 304.96 Bn | 16.12 Bn | 583.00 Mn |
| 3 | Tjx Companies | 162.17 Bn | 139.71 Bn | 5.07 Bn | - |
| 4 | Lowes Companies | 109.50 Bn | 102.46 Bn | 8.58 Bn | - |
| 5 | Ross Stores | 75.29 Bn | 58.21 Bn | 2.12 Bn | - |
| 6 | O Reilly Automotive | 73.37 Bn | 72.46 Bn | 2.52 Bn | 69.87 Mn |
| 7 | Target | 69.83 Bn | 64.42 Bn | 8.94 Bn | 98.00 Mn |
| 8 | Autozone | 51.64 Bn | 50.54 Bn | 2.52 Bn | - |
| 9 | Carvana | 43.37 Bn | 33.86 Bn | 1.38 Bn | 101.00 Mn |
| 10 | JD.com | 36.60 Bn | -83.60 Bn | 8.71 Bn | -103.98 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 69.87 Mn |
| Mar 31, 2026 | 62.75 Mn |
| Dec 31, 2025 | 60.60 Mn |
| Sep 30, 2025 | 59.57 Mn |
| Jun 30, 2025 | 57.34 Mn |
| Mar 31, 2025 | 57.56 Mn |
| Dec 31, 2024 | 55.40 Mn |
| Sep 30, 2024 | 55.17 Mn |
| Jun 30, 2024 | 54.83 Mn |
| Mar 31, 2024 | 57.15 Mn |
| Dec 31, 2023 | 56.15 Mn |
| Sep 30, 2023 | 51.36 Mn |
| Jun 30, 2023 | 49.59 Mn |
| Mar 31, 2023 | 44.57 Mn |
| Dec 31, 2022 | 42.33 Mn |
| Sep 30, 2022 | 43.16 Mn |
| Jun 30, 2022 | 37.38 Mn |
| Mar 31, 2022 | 34.84 Mn |
| Dec 31, 2021 | 34.73 Mn |
| Sep 30, 2021 | 34.87 Mn |
O Reilly Automotive Interest 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=interest-expenses&ticker=ORLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "interest-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=interest-expenses&ticker=ORLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();