Burlington Stores (BURL) Operating Expenses (2012 - 2026)
Burlington Stores (BURL) recorded Operating Expenses of $2.76 billion in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 7.1% from $2.58 billion a year earlier and up 1.7% from the prior quarter.
Burlington Stores (BURL) Operating Expenses (2012 - 2026) Analysis & Trends
On a TTM basis, Burlington Stores' Operating Expenses came in at $11.28 billion as of Aug 1, 2026, up 9.6% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $10.75 billion, up 7.9% from FY2025.
- Annual Operating Expenses has increased for three straight fiscal years, with a five-year compound annual growth rate of 11.6% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $9.96 billion in FY2025 (+7.5%), $9.26 billion in FY2024 (+10.3%), $8.4 billion in FY2023 (-4.4%) and $8.78 billion in FY2022 (+41.5%).
- Quarterly Operating Expenses has ranged from $1.91 billion in fiscal Q1 2023 to $3.23 billion in fiscal Q4 2026 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for 15 consecutive quarters, with growth averaging 8.2% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 38.2% in fiscal Q3 2022, against a decline of 11.2% in fiscal Q3 2023 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $2.71 billion (Q1 2027), $3.23 billion (Q4 2026) and $2.57 billion (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,654.24 Bn | 2,170.93 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 289.19 Bn | 282.43 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 143.39 Bn | 120.94 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.29 Bn | 98.25 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.79 Bn | 58.72 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 72.00 Bn | 66.59 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.61 Bn | 69.69 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 66.52 Bn | 58.12 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 47.57 Bn | 46.47 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Burlington Stores | 16.74 Bn | 13.48 Bn | 1.39 Bn | 2.76 Bn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 2.76 Bn |
| May 2, 2026 | 2.71 Bn |
| Jan 31, 2026 | 3.23 Bn |
| Nov 1, 2025 | 2.57 Bn |
| Aug 2, 2025 | 2.58 Bn |
| May 3, 2025 | 2.37 Bn |
| Feb 1, 2025 | 2.93 Bn |
| Nov 2, 2024 | 2.41 Bn |
| Aug 3, 2024 | 2.37 Bn |
| May 4, 2024 | 2.25 Bn |
| Feb 3, 2024 | 2.81 Bn |
| Oct 28, 2023 | 2.22 Bn |
| Jul 29, 2023 | 2.13 Bn |
| Apr 29, 2023 | 2.09 Bn |
| Jan 28, 2023 | 2.49 Bn |
| Oct 29, 2022 | 2.02 Bn |
| Jul 30, 2022 | 1.97 Bn |
| Apr 30, 2022 | 1.91 Bn |
| Jan 29, 2022 | 2.43 Bn |
| Oct 30, 2021 | 2.27 Bn |
Burlington Stores 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=BURL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BURL", "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=BURL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();