Oxford Industries (OXM) Other Operating Expenses (2010 - 2026)
Oxford Industries' Other Operating Expenses was $7.16 million in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 112.5% from $3.37 million a year earlier and up 24.5% from the prior quarter.
Oxford Industries (OXM) Other Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Oxford Industries' Other Operating Expenses was $18.69 million through Aug 1, 2026, up 5.2% year-over-year; for FY2026 (ended Jan 31, 2026), it was $15.78 million, down 18.3% from FY2025.
- Other Operating Expenses has now declined for four consecutive fiscal years, though with a five-year compound annual growth rate of 2.4% (FY2021 to FY2026).
- In earlier fiscal years, Other Operating Expenses was $19.31 million in FY2025 (-2.0%), $19.71 million in FY2024 (-10.1%), $21.92 million in FY2023 (-33.4%) and $32.92 million in FY2022 (+134.7%).
- The fiscal Q2 2027 figure marks the highest quarterly Other Operating Expenses since fiscal Q1 2025.
- Compared with a year earlier, Other Operating Expenses was higher in three of the last eight quarters, with growth averaging 4.2%.
- The best year-over-year quarter for Other Operating Expenses over five years was fiscal Q3 2022 (growth of 338.7%); the worst was fiscal Q3 2023 (a decline of 70.2%).
- Per Business Quant data, OXM's Other Operating Expenses in the three fiscal quarters before Q2 2027 was $5.75 million (Q1 2027), $2.62 million (Q4 2026) and $3.17 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nike | 52.47 Bn | 18.46 Bn | 5.39 Bn |
| 2 | Tapestry | 23.05 Bn | 19.01 Bn | 1.56 Bn |
| 3 | Ralph Lauren | 21.35 Bn | 13.45 Bn | 1.44 Bn |
| 4 | Deckers Outdoor | 11.12 Bn | 3.99 Bn | - |
| 5 | Lululemon Athletica | 10.25 Bn | 4.50 Bn | 1.46 Bn |
| 6 | Levi Strauss | 7.60 Bn | 4.25 Bn | 979.10 Mn |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn |
| 8 | Birkenstock Holding | 5.97 Bn | 4.27 Bn | 493.89 Mn |
| 9 | Crocs | 5.64 Bn | 5.06 Bn | 700.71 Mn |
| 10 | Oxford Industries | 365.77 Mn | 331.28 Mn | 291.13 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 7.16 Mn |
| May 2, 2026 | 5.75 Mn |
| Jan 31, 2026 | 2.62 Mn |
| Nov 1, 2025 | 3.17 Mn |
| Aug 2, 2025 | 3.37 Mn |
| May 3, 2025 | 6.63 Mn |
| Feb 1, 2025 | 3.80 Mn |
| Nov 2, 2024 | 3.97 Mn |
| Aug 3, 2024 | 4.35 Mn |
| May 4, 2024 | 7.19 Mn |
| Feb 3, 2024 | 3.35 Mn |
| Oct 28, 2023 | 3.86 Mn |
| Jul 29, 2023 | 4.18 Mn |
| Apr 29, 2023 | 8.32 Mn |
| Jan 28, 2023 | 3.91 Mn |
| Oct 29, 2022 | 4.65 Mn |
| Jul 30, 2022 | 6.36 Mn |
| Apr 30, 2022 | 7.01 Mn |
| Jan 29, 2022 | 7.18 Mn |
| Oct 30, 2021 | 15.57 Mn |
Oxford Industries Other 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=other-operating-expenses&ticker=OXM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "OXM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=OXM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();