Oxford Industries (OXM) Gross Margin (2010 - 2026)
Oxford Industries (OXM) recorded Gross Margin of 73.82% in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 12.40 percentage points from 61.42% a year earlier and up 11.51 percentage points from the prior quarter.
Oxford Industries (OXM) Gross Margin (2010 - 2026) Analysis & Trends
On a TTM basis, Oxford Industries' Gross Margin came in at 63.56% as of Aug 1, 2026, up 1.26 percentage points year-over-year; for FY2026 (ended Jan 31, 2026), it was 60.75%, down 2.19 percentage points from FY2025.
- Annual Gross Margin has a five-year change of +5.30 percentage points (FY2021 to FY2026).
- Across earlier fiscal years, Gross Margin came in at 62.94% in FY2025 (-0.41 pp), 63.35% in FY2024 (+0.38 pp), 62.97% in FY2023 (+1.13 pp) and 61.84% in FY2022 (+6.39 pp).
- The fiscal Q2 2027 figure is the highest quarterly Gross Margin in data going back to fiscal Q2 2011.
- On a year-over-year basis, Gross Margin rose in two of the last eight quarters, with an average year-over-year change of +0.17 percentage points.
- Peak year-over-year performance for Gross Margin in the last five years was a gain of 12.40 percentage points in fiscal Q2 2027, against a drop of 3.85 percentage points in fiscal Q4 2026 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at 62.31% (Q1 2027), 56.76% (Q4 2026) and 60.28% (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Gross Margin (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 52.47 Bn | 18.46 Bn | 5.39 Bn | 49.15% |
| 2 | Tapestry | 23.05 Bn | 19.01 Bn | 1.56 Bn | 83.32% |
| 3 | Ralph Lauren | 21.35 Bn | 13.45 Bn | 1.44 Bn | 73.69% |
| 4 | Deckers Outdoor | 11.12 Bn | 3.99 Bn | - | - |
| 5 | Lululemon Athletica | 10.25 Bn | 4.50 Bn | 1.46 Bn | 60.52% |
| 6 | Levi Strauss | 7.60 Bn | 4.25 Bn | 979.10 Mn | 62.68% |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn | 29.05% |
| 8 | Birkenstock Holding | 5.97 Bn | 4.27 Bn | 493.89 Mn | 59.05% |
| 9 | Crocs | 5.64 Bn | 5.06 Bn | 700.71 Mn | 59.41% |
| 10 | Oxford Industries | 365.77 Mn | 331.28 Mn | 291.13 Mn | 73.82% |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 73.82% |
| May 2, 2026 | 62.31% |
| Jan 31, 2026 | 56.76% |
| Nov 1, 2025 | 60.28% |
| Aug 2, 2025 | 61.42% |
| May 3, 2025 | 64.22% |
| Feb 1, 2025 | 60.61% |
| Nov 2, 2024 | 63.15% |
| Aug 3, 2024 | 63.11% |
| May 4, 2024 | 64.88% |
| Feb 3, 2024 | 60.90% |
| Oct 28, 2023 | 62.89% |
| Jul 29, 2023 | 63.93% |
| Apr 29, 2023 | 65.49% |
| Jan 28, 2023 | 60.82% |
| Oct 29, 2022 | 63.15% |
| Jul 30, 2022 | 63.88% |
| Apr 30, 2022 | 64.21% |
| Jan 29, 2022 | 59.17% |
| Oct 30, 2021 | 61.57% |
Oxford Industries Gross Margin 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=gross-margin&ticker=OXM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "gross-margin", "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=gross-margin&ticker=OXM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();