Victoria's Secret (VSXY) Change in Accured Expenses (2020 - 2026)
Victoria's Secret's Change in Accured Expenses came in at $118 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 0.9% from $117 million a year earlier.
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Analysis
Victoria's Secret (VSXY) Change in Accured Expenses (2020 - 2026) Analysis & Trends
Over the trailing twelve months to Aug 1, 2026, Victoria's Secret reported Change in Accured Expenses of $32 million, down 20.0% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $114 million.
- Change in Accured Expenses carries a five-year compound annual growth rate of 18.4% (FY2021 to FY2026).
- Going back by fiscal year, Change in Accured Expenses was -$78 million in FY2025, -$11 million in FY2024, -$163 million in FY2023 and $173 million in FY2022 (+253.1%).
- The fiscal Q2 2027 figure represents the highest quarterly Change in Accured Expenses since fiscal Q3 2022.
- Across the past five years, year-over-year growth in Change in Accured Expenses ran from 0.9% in fiscal Q2 2027 to 560.0% in fiscal Q4 2023.
- Business Quant data shows VSXY's Change in Accured Expenses at -$181 million (Q1 2027), -$18 million (Q4 2026) and $113 million (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 | 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 | Victoria's Secret | 7.34 Bn | 5.91 Bn | 759.00 Mn | 118.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 118.00 Mn |
| May 2, 2026 | -181.00 Mn |
| Jan 31, 2026 | -18.00 Mn |
| Nov 1, 2025 | 113.00 Mn |
| Aug 2, 2025 | 117.00 Mn |
| May 3, 2025 | -98.00 Mn |
| Feb 1, 2025 | -23.00 Mn |
| Nov 2, 2024 | 44.00 Mn |
| Aug 3, 2024 | 75.00 Mn |
| May 4, 2024 | -174.00 Mn |
| Feb 3, 2024 | 111.00 Mn |
| Oct 28, 2023 | -16.00 Mn |
| Jul 29, 2023 | 74.00 Mn |
| Apr 29, 2023 | -180.00 Mn |
| Jan 28, 2023 | 66.00 Mn |
| Oct 29, 2022 | -92.00 Mn |
| Jul 30, 2022 | 63.00 Mn |
| Apr 30, 2022 | -200.00 Mn |
| Jan 29, 2022 | 10.00 Mn |
| Oct 30, 2021 | 249.00 Mn |
API Access
Victoria's Secret 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=VSXY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "VSXY", "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=VSXY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();