Oxford Industries (OXM) Enterprise Value (2010 - 2026)
Oxford Industries (OXM) reported Enterprise Value of $558.96 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 3.0% from $542.76 million a year earlier but down 10.7% from the prior quarter.
Oxford Industries (OXM) Enterprise Value (2010 - 2026) Analysis & Trends
Over the twelve months ended Aug 1, 2026, Oxford Industries' Enterprise Value came in at $533.49 million, up 3.0% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $544.62 million, down 59.1% from FY2025.
- Enterprise Value has declined for three consecutive fiscal years, with a five-year compound annual growth rate of -12.2% (FY2021 to FY2026).
- By fiscal year, Enterprise Value came in at $1.33 billion in FY2025 (-13.0%), $1.53 billion in FY2024 (-18.0%), $1.87 billion in FY2023 (+60.1%) and $1.17 billion in FY2022 (+11.8%).
- Five-year quarterly Enterprise Value spans a low of $540.25 million in fiscal Q3 2026 and a high of $1.87 billion in fiscal Q4 2023.
- Year over year, Enterprise Value gained in 1 of the last eight quarters, with an average decline of 34.0%.
- The high point for year-over-year Enterprise Value in five years was fiscal Q3 2022 (growth of 114.7%); the low point was fiscal Q2 2026 (a decline of 63.8%).
- Per Business Quant data, the three fiscal quarters before Q2 2027 came in at $625.65 million (Q1 2027), $544.62 million (Q4 2026) and $540.25 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nike | 53.14 Bn | 19.13 Bn | 5.39 Bn |
| 2 | Tapestry | 22.87 Bn | 18.83 Bn | 1.56 Bn |
| 3 | Ralph Lauren | 21.39 Bn | 13.49 Bn | 1.44 Bn |
| 4 | Deckers Outdoor | 11.06 Bn | 3.93 Bn | - |
| 5 | Lululemon Athletica | 10.32 Bn | 4.58 Bn | 1.46 Bn |
| 6 | Levi Strauss | 7.62 Bn | 4.28 Bn | 979.10 Mn |
| 7 | Gildan Activewear | 6.55 Bn | 5.54 Bn | 459.76 Mn |
| 8 | Birkenstock Holding | 6.07 Bn | 4.38 Bn | 493.89 Mn |
| 9 | Crocs | 5.90 Bn | 5.31 Bn | 700.71 Mn |
| 10 | Oxford Industries | 374.46 Mn | 339.97 Mn | 291.13 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 558.96 Mn |
| May 2, 2026 | 625.65 Mn |
| Jan 31, 2026 | 544.62 Mn |
| Nov 1, 2025 | 540.25 Mn |
| Aug 2, 2025 | 542.76 Mn |
| May 3, 2025 | 738.30 Mn |
| Feb 1, 2025 | 1.33 Bn |
| Nov 2, 2024 | 1.14 Bn |
| Aug 3, 2024 | 1.50 Bn |
| May 4, 2024 | 1.70 Bn |
| Feb 3, 2024 | 1.53 Bn |
| Oct 28, 2023 | 1.33 Bn |
| Jul 29, 2023 | 1.67 Bn |
| Apr 29, 2023 | 1.61 Bn |
| Jan 28, 2023 | 1.87 Bn |
| Oct 29, 2022 | 1.57 Bn |
| Jul 30, 2022 | 1.33 Bn |
| Apr 30, 2022 | 1.26 Bn |
| Jan 29, 2022 | 1.17 Bn |
| Oct 30, 2021 | 1.38 Bn |
Oxford Industries Enterprise Value 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=enterprise-value&ticker=OXM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "enterprise-value", "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=enterprise-value&ticker=OXM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();