Dollar General (DG) Change in Accured Expenses (2010 - 2026)
Dollar General's Change in Accured Expenses was $188.24 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), up 10.5% from $170.3 million a year earlier.
Dollar General (DG) Change in Accured Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Dollar General's Change in Accured Expenses was $157.36 million through Jul 31, 2026, up 5.4% year-over-year; for FY2026 (ended Jan 30, 2026), it came in at $249.97 million, up 172.3% from FY2025.
- Change in Accured Expenses shows a five-year compound annual growth rate of -8.4% (FY2021 to FY2026).
- In earlier fiscal years, Change in Accured Expenses was $91.81 million in FY2025, -$39.19 million in FY2024, -$25.41 million in FY2023 and -$37.33 million in FY2022.
- The fiscal Q2 2027 figure marks the highest quarterly Change in Accured Expenses since fiscal Q2 2021.
- The best year-over-year quarter for Change in Accured Expenses over five years was fiscal Q3 2026 (growth of 335.3%); the worst was fiscal Q3 2023 (a decline of 49.1%).
- Per Business Quant data, DG's Change in Accured Expenses in the three fiscal quarters before Q2 2027 was -$113.55 million (Q1 2027), -$39.99 million (Q4 2026) and $122.65 million (Q3 2026).
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 | 188.24 Mn |
| May 1, 2026 | -113.55 Mn |
| Jan 30, 2026 | -39.99 Mn |
| Oct 31, 2025 | 122.65 Mn |
| Aug 1, 2025 | 170.30 Mn |
| May 2, 2025 | -2.99 Mn |
| Jan 31, 2025 | -46.12 Mn |
| Nov 1, 2024 | 28.18 Mn |
| Aug 2, 2024 | 94.95 Mn |
| May 3, 2024 | 14.81 Mn |
| Feb 2, 2024 | -42.99 Mn |
| Nov 3, 2023 | 16.24 Mn |
| Aug 4, 2023 | 164.37 Mn |
| May 5, 2023 | -176.80 Mn |
| Feb 3, 2023 | -79.54 Mn |
| Oct 28, 2022 | 31.75 Mn |
| Jul 29, 2022 | 138.77 Mn |
| Apr 29, 2022 | -116.38 Mn |
| Jan 28, 2022 | -74.24 Mn |
| Oct 29, 2021 | 62.39 Mn |
Dollar General 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=DG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "DG", "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=DG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();