Xpo (XPO) Change in Accured Expenses (2010 - 2026)
Xpo's Change in Accured Expenses was $30 million in Q2 2026, compared with -$9 million a year earlier and down 38.8% from the prior quarter.
Xpo (XPO) Change in Accured Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Xpo's Change in Accured Expenses was $115 million through Jun 30, 2026; for FY2025, it was $62 million.
- Change in Accured Expenses shows a five-year compound annual growth rate of -13.2% (FY2020 to FY2025).
- In earlier years, Change in Accured Expenses was -$33 million in FY2024, $4 million in FY2023 (-90.5%), $42 million in FY2022 (+110.0%) and $20 million in FY2021 (-84.1%).
- Quarterly Change in Accured Expenses has moved between -$151 million (Q4 2021) and $116 million (Q1 2022) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in three of the last four quarters, with growth averaging 137.6%.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q3 2025 (growth of 525.0%); the worst was Q2 2023 (a decline of 90.2%).
- Per Business Quant data, XPO's Change in Accured Expenses in the three quarters before Q2 2026 was $49 million (Q1 2026), -$14 million (Q4 2025) and $50 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Union Pacific | 173.89 Bn | 166.14 Bn | - | -30.00 Mn |
| 2 | Csx | 94.27 Bn | 89.49 Bn | - | - |
| 3 | United Parcel Service | 86.13 Bn | 63.03 Bn | - | 147.00 Mn |
| 4 | Canadian Pacific Kansas City | 79.52 Bn | 78.54 Bn | - | - |
| 5 | Norfolk Southern | 74.18 Bn | 68.65 Bn | - | - |
| 6 | Fedex | 71.02 Bn | 36.96 Bn | - | 1.21 Bn |
| 7 | Delta Air Lines | 50.26 Bn | 32.44 Bn | - | - |
| 8 | Old Dominion Freight Line | 38.08 Bn | 37.35 Bn | - | - |
| 9 | United Airlines Holdings | 31.84 Bn | -25.85 Bn | - | - |
| 10 | Xpo | 21.51 Bn | 20.33 Bn | - | 30.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 30.00 Mn |
| Mar 31, 2026 | 49.00 Mn |
| Dec 31, 2025 | -14.00 Mn |
| Sep 30, 2025 | 50.00 Mn |
| Jun 30, 2025 | -9.00 Mn |
| Mar 31, 2025 | 35.00 Mn |
| Dec 31, 2024 | -54.00 Mn |
| Sep 30, 2024 | 8.00 Mn |
| Jun 30, 2024 | -8.00 Mn |
| Mar 31, 2024 | 21.00 Mn |
| Dec 31, 2023 | -66.00 Mn |
| Sep 30, 2023 | 43.00 Mn |
| Jun 30, 2023 | 5.00 Mn |
| Mar 31, 2023 | 22.00 Mn |
| Dec 31, 2022 | -85.00 Mn |
| Sep 30, 2022 | -40.00 Mn |
| Jun 30, 2022 | 51.00 Mn |
| Mar 31, 2022 | 116.00 Mn |
| Dec 31, 2021 | -151.00 Mn |
| Sep 30, 2021 | 51.00 Mn |
Xpo Change in Accured 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=change-in-accured-expenses&ticker=XPO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "XPO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=XPO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();