Destination Xl (DXLG) Operating Expenses (2010 - 2026)
Destination Xl's Operating Expenses came in at $51.47 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), unchanged from $51.48 million a year earlier and down 0.4% from the prior quarter.
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Analysis
Destination Xl (DXLG) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Aug 1, 2026, Destination Xl reported Operating Expenses of $207.75 million, down 0.2% year-over-year; for FY2026 (ended Jan 31, 2026), it was $207.15 million, down 3.0% from FY2025.
- Operating Expenses carries a five-year compound annual growth rate of 4.6% (FY2021 to FY2026).
- Going back by fiscal year, Operating Expenses was $213.46 million in FY2025 (+1.4%), $210.48 million in FY2024 (-1.7%), $214.01 million in FY2023 (+13.9%) and $187.84 million in FY2022 (+13.6%).
- The five-year range for quarterly Operating Expenses is $45.02 million (fiscal Q3 2022) to $58.22 million (fiscal Q4 2023).
- Year-over-year, Operating Expenses increased in three of the last eight quarters, with an average decline of 1.8%.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q4 2022 (growth of 30.1%), and the weakest in fiscal Q2 2026 (a decline of 9.8%).
- Business Quant data shows DXLG's Operating Expenses at $51.69 million (Q1 2027), $55.33 million (Q4 2026) and $49.25 million (Q3 2026) in the three fiscal quarters before Q2 2027.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,686.58 Bn | 2,203.28 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 283.87 Bn | 277.11 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 145.82 Bn | 123.36 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 103.43 Bn | 96.39 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.61 Bn | 57.54 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.16 Bn | 65.74 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 69.71 Bn | 68.80 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 68.78 Bn | 60.38 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.23 Bn | 45.13 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Destination Xl | 24.40 Mn | -67.74 Mn | 53.41 Mn | 51.47 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 51.47 Mn |
| May 2, 2026 | 51.69 Mn |
| Jan 31, 2026 | 55.33 Mn |
| Nov 1, 2025 | 49.25 Mn |
| Aug 2, 2025 | 51.48 Mn |
| May 3, 2025 | 51.08 Mn |
| Feb 1, 2025 | 54.64 Mn |
| Nov 2, 2024 | 50.98 Mn |
| Aug 3, 2024 | 57.05 Mn |
| May 4, 2024 | 50.80 Mn |
| Feb 3, 2024 | 56.45 Mn |
| Oct 28, 2023 | 51.36 Mn |
| Jul 29, 2023 | 50.91 Mn |
| Apr 29, 2023 | 51.76 Mn |
| Jan 28, 2023 | 58.22 Mn |
| Oct 29, 2022 | 52.15 Mn |
| Jul 30, 2022 | 53.41 Mn |
| Apr 30, 2022 | 50.23 Mn |
| Jan 29, 2022 | 56.06 Mn |
| Oct 30, 2021 | 45.02 Mn |
API Access
Destination Xl 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=DXLG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DXLG", "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=DXLG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();