Walmart (WMT) Change in Accured Expenses (2009 - 2026)
Walmart's Change in Accured Expenses came in at $1.9 billion for fiscal Q2 2027 (quarter ended Jul 31, 2026), down 12.5% from $2.17 billion a year earlier.
Walmart (WMT) Change in Accured Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jul 31, 2026, Walmart reported Change in Accured Expenses of $1.61 billion, up 379.5% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $1.61 billion, up 324.0% from FY2025.
- Change in Accured Expenses carries a five-year compound annual growth rate of -19.0% (FY2021 to FY2026).
- Going back by fiscal year, Change in Accured Expenses was $379 million in FY2025, -$1.32 billion in FY2024, $4.39 billion in FY2023 (+212.9%) and $1.4 billion in FY2022 (-69.6%).
- The five-year range for quarterly Change in Accured Expenses is -$4.95 billion (fiscal Q1 2023) to $3.79 billion (fiscal Q3 2023).
- Year-over-year, Change in Accured Expenses increased in 1 of the last five quarters, with growth averaging 28.8%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in fiscal Q3 2023 (growth of 449.7%), and the weakest in fiscal Q4 2025 (a decline of 60.1%).
- Business Quant data shows WMT's Change in Accured Expenses at -$3.35 billion (Q1 2027), $713 million (Q4 2026) and $2.35 billion (Q3 2026) in the three fiscal quarters before Q2 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 827.17 Bn | 789.87 Bn | 49.13 Bn | 1.90 Bn |
| 2 | Costco Wholesale | 408.32 Bn | 337.62 Bn | 9.01 Bn | - |
| 3 | Sysco | 37.11 Bn | 31.36 Bn | 4.13 Bn | 114.00 Mn |
| 4 | Kroger | 34.86 Bn | 21.01 Bn | 7.86 Bn | - |
| 5 | Dollar General | 26.24 Bn | 20.91 Bn | 3.68 Bn | 188.24 Mn |
| 6 | Caseys General Stores | 22.83 Bn | 20.83 Bn | 1.24 Bn | -50.26 Mn |
| 7 | Dollar Tree | 21.05 Bn | 17.67 Bn | 2.10 Bn | - |
| 8 | US Foods Holding | 20.97 Bn | 20.76 Bn | 1.92 Bn | 5.00 Mn |
| 9 | Tractor Supply | 16.22 Bn | 15.39 Bn | 1.68 Bn | 272.58 Mn |
| 10 | Performance Food | 14.65 Bn | 14.43 Bn | 2.17 Bn | 181.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 1.90 Bn |
| Apr 30, 2026 | -3.35 Bn |
| Jan 31, 2026 | 713.00 Mn |
| Oct 31, 2025 | 2.35 Bn |
| Jul 31, 2025 | 2.17 Bn |
| Apr 30, 2025 | -3.63 Bn |
| Jan 31, 2025 | 1.19 Bn |
| Oct 31, 2024 | 603.00 Mn |
| Jul 31, 2024 | 3.24 Bn |
| Apr 30, 2024 | -4.65 Bn |
| Jan 31, 2024 | 2.97 Bn |
| Oct 31, 2023 | -2.93 Bn |
| Jul 31, 2023 | 3.08 Bn |
| Apr 30, 2023 | -4.45 Bn |
| Jan 31, 2023 | 3.04 Bn |
| Oct 31, 2022 | 3.79 Bn |
| Jul 31, 2022 | 2.51 Bn |
| Apr 30, 2022 | -4.95 Bn |
| Jan 31, 2022 | 2.13 Bn |
| Oct 31, 2021 | 690.00 Mn |
Walmart 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=WMT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "WMT", "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=WMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();