Oxford Industries (OXM) Free Cash Flow (2010 - 2026)
Oxford Industries (OXM) reported Free Cash Flow of $80.63 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 54.1% from $52.31 million a year earlier.
Oxford Industries (OXM) Free Cash Flow (2010 - 2026) Analysis & Trends
Over the twelve months ended Aug 1, 2026, Oxford Industries' Free Cash Flow came in at $52.13 million, up 215.2% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $11.31 million, down 81.1% from FY2025.
- Free Cash Flow has a five-year compound annual growth rate of -27.1% (FY2021 to FY2026).
- By fiscal year, Free Cash Flow came in at $59.8 million in FY2025 (-64.9%), $170.19 million in FY2024 (+115.6%), $78.94 million in FY2023 (-52.5%) and $166.11 million in FY2022 (+202.4%).
- The fiscal Q2 2027 figure ranks as the highest quarterly Free Cash Flow since fiscal Q2 2024.
- Year over year, Free Cash Flow gained in two of the last four quarters, with growth averaging 5.9%.
- The high point for year-over-year Free Cash Flow in five years was fiscal Q1 2024 (growth of 171.9%); the low point was fiscal Q1 2023 (a decline of 63.4%).
- Per Business Quant data, the three fiscal quarters before Q2 2027 came in at -$14.87 million (Q1 2027), $34.28 million (Q4 2026) and -$47.92 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FCF (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 52.47 Bn | 18.46 Bn | 5.39 Bn | 1.50 Bn |
| 2 | Tapestry | 23.05 Bn | 19.01 Bn | 1.56 Bn | 469.00 Mn |
| 3 | Ralph Lauren | 21.35 Bn | 13.45 Bn | 1.44 Bn | 285.90 Mn |
| 4 | Deckers Outdoor | 11.12 Bn | 3.99 Bn | - | - |
| 5 | Lululemon Athletica | 10.25 Bn | 4.50 Bn | 1.46 Bn | 225.16 Mn |
| 6 | Levi Strauss | 7.60 Bn | 4.25 Bn | 979.10 Mn | 230.90 Mn |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn | 367.29 Mn |
| 8 | Birkenstock Holding | 5.97 Bn | 4.27 Bn | 493.89 Mn | 316.96 Mn |
| 9 | Crocs | 5.64 Bn | 5.06 Bn | 700.71 Mn | 330.97 Mn |
| 10 | Oxford Industries | 365.77 Mn | 331.28 Mn | 291.13 Mn | 80.63 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 80.63 Mn |
| May 2, 2026 | -14.87 Mn |
| Jan 31, 2026 | 34.28 Mn |
| Nov 1, 2025 | -47.92 Mn |
| Aug 2, 2025 | 52.31 Mn |
| May 3, 2025 | -27.37 Mn |
| Feb 1, 2025 | 48.53 Mn |
| Nov 2, 2024 | -56.93 Mn |
| Aug 3, 2024 | 47.18 Mn |
| May 4, 2024 | 21.03 Mn |
| Feb 3, 2024 | 55.28 Mn |
| Oct 28, 2023 | -6.19 Mn |
| Jul 29, 2023 | 85.20 Mn |
| Apr 29, 2023 | 35.90 Mn |
| Jan 28, 2023 | 25.02 Mn |
| Oct 29, 2022 | -16.96 Mn |
| Jul 30, 2022 | 57.68 Mn |
| Apr 30, 2022 | 13.20 Mn |
| Jan 29, 2022 | 34.16 Mn |
| Oct 30, 2021 | -809,000.00 |
Oxford Industries Free Cash Flow 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=free-cash-flow&ticker=OXM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "free-cash-flow", "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=free-cash-flow&ticker=OXM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();