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.
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Analysis
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 Set
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
Download Data
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 |
API Access
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_KEYimport 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();