Oxford Industries (OXM) Return on Sales [ROS] (2010 - 2026)
Oxford Industries (OXM) posted Return on Sales [ROS] of 17.45% for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 11.15 percentage points from 6.30% a year earlier and up 11.74 percentage points from the prior quarter.
Oxford Industries (OXM) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
For the trailing twelve months through Aug 1, 2026, Return on Sales [ROS] at Oxford Industries was -0.12%, down 5.18 percentage points year-over-year; for FY2026 (ended Jan 31, 2026), it was -2.12%, down 9.97 percentage points from FY2025.
- Annual Return on Sales [ROS] shows a five-year change of +14.42 percentage points (FY2021 to FY2026).
- In prior fiscal years, Oxford Industries' Return on Sales [ROS] was 7.85% in FY2025 (+2.70 pp), 5.15% in FY2024 (-10.35 pp), 15.50% in FY2023 (+1.01 pp) and 14.49% in FY2022 (+31.03 pp).
- The fiscal Q2 2027 figure stands as the highest quarterly Return on Sales [ROS] since fiscal Q1 2024.
- On a year-over-year basis, Return on Sales [ROS] increased in two of the last eight quarters, with an average year-over-year change of -2.07 percentage points.
- The strongest year-over-year quarter for Return on Sales [ROS] in the past five years was fiscal Q4 2025, with a gain of 25.34 percentage points; the weakest was fiscal Q4 2024, with a drop of 30.63 percentage points.
- According to Business Quant data, Return on Sales [ROS] for the three prior fiscal quarters was 5.71% (Q1 2027), -2.08% (Q4 2026) and -27.69% (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 50.34 Bn | 16.54 Bn | 4.80 Bn | 7.92% |
| 2 | Tapestry | 23.66 Bn | 19.62 Bn | 1.56 Bn | 23.57% |
| 3 | Ralph Lauren | 21.85 Bn | 13.95 Bn | 1.44 Bn | 17.47% |
| 4 | Deckers Outdoor | 11.26 Bn | 4.14 Bn | - | - |
| 5 | Lululemon Athletica | 10.07 Bn | 4.32 Bn | 1.46 Bn | 18.78% |
| 6 | Levi Strauss | 7.67 Bn | 4.32 Bn | 979.10 Mn | 7.82% |
| 7 | Gildan Activewear | 6.27 Bn | 5.26 Bn | 459.76 Mn | 11.12% |
| 8 | Birkenstock Holding | 6.13 Bn | 4.43 Bn | 493.89 Mn | 28.22% |
| 9 | Crocs | 5.68 Bn | 5.09 Bn | 700.71 Mn | 24.22% |
| 10 | Oxford Industries | 373.71 Mn | 339.22 Mn | 291.13 Mn | 17.45% |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 17.45% |
| May 2, 2026 | 5.71% |
| Jan 31, 2026 | -2.08% |
| Nov 1, 2025 | -27.69% |
| Aug 2, 2025 | 6.30% |
| May 3, 2025 | 9.22% |
| Feb 1, 2025 | 5.20% |
| Nov 2, 2024 | -2.03% |
| Aug 3, 2024 | 12.51% |
| May 4, 2024 | 13.17% |
| Feb 3, 2024 | -20.14% |
| Oct 28, 2023 | 4.43% |
| Jul 29, 2023 | 16.10% |
| Apr 29, 2023 | 19.11% |
| Jan 28, 2023 | 10.49% |
| Oct 29, 2022 | 8.73% |
| Jul 30, 2022 | 20.74% |
| Apr 30, 2022 | 21.55% |
| Jan 29, 2022 | 10.67% |
| Oct 30, 2021 | 12.36% |
Oxford Industries Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=OXM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=OXM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();