Murphy USA (MUSA) Operating Expenses (2012 - 2026)
Murphy USA's Operating Expenses was $6.5 billion in Q2 2026, up 35.9% from $4.79 billion a year earlier and up 40.9% from the prior quarter.
Murphy USA (MUSA) Operating Expenses (2012 - 2026) Analysis & Trends
On a trailing twelve-month basis, Murphy USA's Operating Expenses was $20.56 billion through Jun 30, 2026, up 9.6% year-over-year; for FY2025, it was $18.66 billion, down 4.3% from FY2024.
- Operating Expenses has now declined for three consecutive years, though with a five-year compound annual growth rate of 11.8% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $19.5 billion in FY2024 (-5.8%), $20.7 billion in FY2023 (-7.9%), $22.48 billion in FY2022 (+34.1%) and $16.76 billion in FY2021 (+56.5%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q2 2022.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 0.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2021 (growth of 66.4%); the worst was Q2 2023 (a decline of 17.2%).
- Per Business Quant data, MUSA's Operating Expenses in the three quarters before Q2 2026 was $4.61 billion (Q1 2026), $4.53 billion (Q4 2025) and $4.91 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 938.89 Bn | 895.32 Bn | 49.13 Bn | 39.75 Bn |
| 2 | Costco Wholesale | 441.44 Bn | 364.72 Bn | 12.19 Bn | 8.39 Bn |
| 3 | Sysco | 39.34 Bn | 33.59 Bn | 4.13 Bn | 3.15 Bn |
| 4 | Kroger | 38.49 Bn | 24.64 Bn | 7.86 Bn | 198.00 Mn |
| 5 | Dollar General | 29.44 Bn | 24.12 Bn | 3.68 Bn | 2.91 Bn |
| 6 | Caseys General Stores | 25.45 Bn | 23.44 Bn | 1.24 Bn | 754.11 Mn |
| 7 | Dollar Tree | 23.97 Bn | 20.59 Bn | 2.10 Bn | 1.43 Bn |
| 8 | US Foods Holding | 22.39 Bn | 22.19 Bn | 1.92 Bn | 1.48 Bn |
| 9 | Tractor Supply | 17.17 Bn | 16.33 Bn | 1.68 Bn | 1.02 Bn |
| 10 | Murphy USA | 9.82 Bn | 9.46 Bn | 746.50 Mn | 6.50 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.50 Bn |
| Mar 31, 2026 | 4.61 Bn |
| Dec 31, 2025 | 4.53 Bn |
| Sep 30, 2025 | 4.91 Bn |
| Jun 30, 2025 | 4.79 Bn |
| Mar 31, 2025 | 4.44 Bn |
| Dec 31, 2024 | 4.51 Bn |
| Sep 30, 2024 | 5.02 Bn |
| Jun 30, 2024 | 5.23 Bn |
| Mar 31, 2024 | 4.74 Bn |
| Dec 31, 2023 | 4.85 Bn |
| Sep 30, 2023 | 5.55 Bn |
| Jun 30, 2023 | 5.39 Bn |
| Mar 31, 2023 | 4.91 Bn |
| Dec 31, 2022 | 5.19 Bn |
| Sep 30, 2022 | 5.88 Bn |
| Jun 30, 2022 | 6.51 Bn |
| Mar 31, 2022 | 4.90 Bn |
| Dec 31, 2021 | 4.61 Bn |
| Sep 30, 2021 | 4.44 Bn |
Murphy USA 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=MUSA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MUSA", "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=MUSA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();