American Eagle Outfitters (AEO) Change in Accured Expenses (2009 - 2026)
American Eagle Outfitters' Change in Accured Expenses was -$8.13 million in fiscal Q2 2027 (quarter ended Aug 1, 2026), compared with -$9.04 million a year earlier.
American Eagle Outfitters (AEO) Change in Accured Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, American Eagle Outfitters' Change in Accured Expenses was $9.73 million through Aug 1, 2026; for FY2026 (ended Jan 31, 2026), it was -$32.1 million.
- In earlier fiscal years, Change in Accured Expenses was -$38.05 million in FY2025, $100.22 million in FY2024, -$90.11 million in FY2023 and $50.44 million in FY2022 (-47.0%).
- Quarterly Change in Accured Expenses has moved between -$107.41 million (fiscal Q1 2023) and $55.64 million (fiscal Q4 2024) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in 1 of the last four quarters, with an average decline of 23.0%.
- The best year-over-year quarter for Change in Accured Expenses over five years was fiscal Q4 2024 (growth of 262.4%); the worst was fiscal Q3 2022 (a decline of 91.6%).
- Per Business Quant data, AEO's Change in Accured Expenses in the three fiscal quarters before Q2 2027 was -$14.45 million (Q1 2027), $10.36 million (Q4 2026) and $21.96 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,712.14 Bn | 2,228.84 Bn | 104.83 Bn | -2.02 Bn |
| 2 | Home Depot | 282.27 Bn | 275.52 Bn | 16.12 Bn | -512.00 Mn |
| 3 | Tjx Companies | 146.16 Bn | 123.70 Bn | 5.07 Bn | 415.00 Mn |
| 4 | Lowes Companies | 101.42 Bn | 94.39 Bn | 8.58 Bn | - |
| 5 | Ross Stores | 73.06 Bn | 55.98 Bn | 2.12 Bn | - |
| 6 | Target | 70.86 Bn | 65.45 Bn | 8.94 Bn | 595.00 Mn |
| 7 | Carvana | 70.11 Bn | 61.71 Bn | 1.38 Bn | 199.00 Mn |
| 8 | O Reilly Automotive | 69.29 Bn | 68.38 Bn | 2.52 Bn | - |
| 9 | Autozone | 45.61 Bn | 44.51 Bn | 2.52 Bn | 111.71 Mn |
| 10 | American Eagle Outfitters | 2.97 Bn | 2.37 Bn | 672.06 Mn | -8.13 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | -8.13 Mn |
| May 2, 2026 | -14.45 Mn |
| Jan 31, 2026 | 10.36 Mn |
| Nov 1, 2025 | 21.96 Mn |
| Aug 2, 2025 | -9.04 Mn |
| May 3, 2025 | -55.38 Mn |
| Feb 1, 2025 | 23.27 Mn |
| Nov 2, 2024 | 35.44 Mn |
| Aug 3, 2024 | -8.83 Mn |
| May 4, 2024 | -87.93 Mn |
| Feb 3, 2024 | 55.64 Mn |
| Oct 28, 2023 | 22.20 Mn |
| Jul 29, 2023 | 30.79 Mn |
| Apr 29, 2023 | -8.40 Mn |
| Jan 28, 2023 | 15.35 Mn |
| Oct 29, 2022 | -14.33 Mn |
| Jul 30, 2022 | 16.27 Mn |
| Apr 30, 2022 | -107.41 Mn |
| Jan 29, 2022 | 23.95 Mn |
| Oct 30, 2021 | 9.86 Mn |
American Eagle Outfitters 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=AEO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "AEO", "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=AEO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();