Custom Truck One Source (CTOS) Operating Expenses (2017 - 2026)
Custom Truck One Source's Operating Expenses came in at $77.36 million for Q2 2026, up 3.7% from $74.61 million a year earlier and up 8.1% from the prior quarter.
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Analysis
Custom Truck One Source (CTOS) Operating Expenses (2017 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Custom Truck One Source reported Operating Expenses of $288.16 million, up 7.6% year-over-year; for FY2025, it was $286.95 million, up 8.7% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 37.1% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $263.91 million in FY2024 (-6.8%), $283.31 million in FY2023 (+1.0%), $280.44 million in FY2022 (+11.3%) and $251.98 million in FY2021 (+325.7%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses since Q2 2021.
- Year-over-year, Operating Expenses increased in four of the last eight quarters, with growth averaging 1.8%.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 561.3%), and the weakest in Q4 2024 (a decline of 30.2%).
- Business Quant data shows CTOS's Operating Expenses at $71.59 million (Q1 2026), $71.08 million (Q4 2025) and $68.12 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | United Rentals | 65.40 Bn | 64.16 Bn | 1.73 Bn | 1.18 Bn |
| 2 | W.W. Grainger | 63.07 Bn | 60.67 Bn | 1.98 Bn | 1.18 Bn |
| 3 | Fastenal | 59.20 Bn | 58.13 Bn | 1.06 Bn | 561.80 Mn |
| 4 | Ferguson Enterprises | 44.13 Bn | 41.34 Bn | 2.32 Bn | 1.61 Bn |
| 5 | Sunbelt Rentals Holdings | 31.58 Bn | 31.46 Bn | 1.25 Bn | 989.00 Mn |
| 6 | Reliance | 21.32 Bn | 20.36 Bn | 1.30 Bn | 4.19 Bn |
| 7 | Wesco International | 16.71 Bn | 14.03 Bn | 1.46 Bn | 1.02 Bn |
| 8 | Applied Industrial Technologies | 12.36 Bn | 12.23 Bn | 411.22 Mn | 251.91 Mn |
| 9 | Watsco | 11.52 Bn | 9.20 Bn | 578.93 Mn | 348.99 Mn |
| 10 | Custom Truck One Source | 2.07 Bn | 2.03 Bn | 123.97 Mn | 77.36 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 77.36 Mn |
| Mar 31, 2026 | 71.59 Mn |
| Dec 31, 2025 | 71.08 Mn |
| Sep 30, 2025 | 68.12 Mn |
| Jun 30, 2025 | 74.61 Mn |
| Mar 31, 2025 | 73.13 Mn |
| Dec 31, 2024 | 51.18 Mn |
| Sep 30, 2024 | 68.79 Mn |
| Jun 30, 2024 | 71.59 Mn |
| Mar 31, 2024 | 72.34 Mn |
| Dec 31, 2023 | 73.35 Mn |
| Sep 30, 2023 | 69.15 Mn |
| Jun 30, 2023 | 71.04 Mn |
| Mar 31, 2023 | 69.77 Mn |
| Dec 31, 2022 | 76.68 Mn |
| Sep 30, 2022 | 65.07 Mn |
| Jun 30, 2022 | 64.01 Mn |
| Mar 31, 2022 | 74.69 Mn |
| Dec 31, 2021 | 68.01 Mn |
| Sep 30, 2021 | 70.57 Mn |
API Access
Custom Truck One Source 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=CTOS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CTOS", "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=CTOS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();