Victoria's Secret (VSXY) Operating Expenses (2020 - 2026)
Victoria's Secret's Operating Expenses was $502 million in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 5.0% from $478 million a year earlier but down 1.4% from the prior quarter.
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Analysis
Victoria's Secret (VSXY) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Victoria's Secret's Operating Expenses was $2.19 billion through Aug 1, 2026, up 10.0% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $2.11 billion, up 7.0% from FY2025.
- Operating Expenses shows a five-year compound annual growth rate of 4.8% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $1.97 billion in FY2025 (-1.1%), $2 billion in FY2024 (+12.1%), $1.78 billion in FY2023 (-5.8%) and $1.89 billion in FY2022 (+13.0%).
- Quarterly Operating Expenses has moved between $414 million (fiscal Q3 2023) and $626 million (fiscal Q4 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for five straight quarters, with growth averaging 5.6% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q3 2022 (growth of 23.5%); the worst was fiscal Q3 2023 (a decline of 9.4%).
- Per Business Quant data, VSXY's Operating Expenses in the three fiscal quarters before Q2 2027 was $509 million (Q1 2027), $626 million (Q4 2026) and $555 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Victoria's Secret | 7.14 Bn | 5.71 Bn | 759.00 Mn | 502.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 502.00 Mn |
| May 2, 2026 | 509.00 Mn |
| Jan 31, 2026 | 626.00 Mn |
| Nov 1, 2025 | 555.00 Mn |
| Aug 2, 2025 | 478.00 Mn |
| May 3, 2025 | 454.00 Mn |
| Feb 1, 2025 | 545.00 Mn |
| Nov 2, 2024 | 515.00 Mn |
| Aug 3, 2024 | 439.00 Mn |
| May 4, 2024 | 475.00 Mn |
| Feb 3, 2024 | 567.00 Mn |
| Oct 28, 2023 | 494.00 Mn |
| Jul 29, 2023 | 461.00 Mn |
| Apr 29, 2023 | 474.00 Mn |
| Jan 28, 2023 | 500.00 Mn |
| Oct 29, 2022 | 414.00 Mn |
| Jul 30, 2022 | 437.00 Mn |
| Apr 30, 2022 | 428.00 Mn |
| Jan 29, 2022 | 519.00 Mn |
| Oct 30, 2021 | 457.00 Mn |
API Access
Victoria's Secret Operating 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=operating-expenses&ticker=VSXY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-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=operating-expenses&ticker=VSXY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();