Oxford Industries (OXM) Operating Income (2010 - 2026)
Oxford Industries' Operating Income was $68.82 million in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 170.8% from $25.41 million a year earlier and up 207.7% from the prior quarter.
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Analysis
Oxford Industries (OXM) Operating Income (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Oxford Industries' Operating Income was -$1.72 million through Aug 1, 2026; for FY2026 (ended Jan 31, 2026), it was -$31.28 million.
- In earlier fiscal years, Operating Income was $119.04 million in FY2025 (+47.0%), $80.98 million in FY2024 (-63.0%), $218.77 million in FY2023 (+32.2%) and $165.5 million in FY2022.
- The fiscal Q2 2027 figure marks the highest quarterly Operating Income since fiscal Q1 2024.
- Compared with a year earlier, Operating Income was higher in 1 of the last four quarters, with growth averaging 12.5%.
- The best year-over-year quarter for Operating Income over five years was fiscal Q2 2027 (growth of 170.8%); the worst was fiscal Q2 2026 (a decline of 51.6%).
- Per Business Quant data, OXM's Operating Income in the three fiscal quarters before Q2 2027 was $22.36 million (Q1 2027), -$7.8 million (Q4 2026) and -$85.1 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Op. Inc (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 53.14 Bn | 19.13 Bn | 5.39 Bn | 1.31 Bn |
| 2 | Tapestry | 22.87 Bn | 18.83 Bn | 1.56 Bn | 442.30 Mn |
| 3 | Ralph Lauren | 21.39 Bn | 13.49 Bn | 1.44 Bn | 342.40 Mn |
| 4 | Deckers Outdoor | 11.06 Bn | 3.93 Bn | - | - |
| 5 | Lululemon Athletica | 10.32 Bn | 4.58 Bn | 1.46 Bn | 453.65 Mn |
| 6 | Levi Strauss | 7.62 Bn | 4.28 Bn | 979.10 Mn | 122.20 Mn |
| 7 | Gildan Activewear | 6.55 Bn | 5.54 Bn | 459.76 Mn | 175.90 Mn |
| 8 | Birkenstock Holding | 6.07 Bn | 4.38 Bn | 493.89 Mn | 236.02 Mn |
| 9 | Crocs | 5.90 Bn | 5.31 Bn | 700.71 Mn | 285.68 Mn |
| 10 | Oxford Industries | 374.46 Mn | 339.97 Mn | 291.13 Mn | 68.82 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 68.82 Mn |
| May 2, 2026 | 22.36 Mn |
| Jan 31, 2026 | -7.80 Mn |
| Nov 1, 2025 | -85.10 Mn |
| Aug 2, 2025 | 25.41 Mn |
| May 3, 2025 | 36.21 Mn |
| Feb 1, 2025 | 20.32 Mn |
| Nov 2, 2024 | -6.24 Mn |
| Aug 3, 2024 | 52.51 Mn |
| May 4, 2024 | 52.45 Mn |
| Feb 3, 2024 | -81.45 Mn |
| Oct 28, 2023 | 14.46 Mn |
| Jul 29, 2023 | 67.67 Mn |
| Apr 29, 2023 | 80.30 Mn |
| Jan 28, 2023 | 40.11 Mn |
| Oct 29, 2022 | 27.32 Mn |
| Jul 30, 2022 | 75.37 Mn |
| Apr 30, 2022 | 75.98 Mn |
| Jan 29, 2022 | 32.01 Mn |
| Oct 30, 2021 | 30.61 Mn |
API Access
Oxford Industries Operating Income 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-income&ticker=OXM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-income", "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=operating-income&ticker=OXM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();