G Iii Apparel (GIII) EBITDA (2010 - 2026)
G Iii Apparel (GIII) recorded EBITDA of $19.03 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), down 19.5% from $23.63 million a year earlier and down 79.4% from the prior quarter.
Powered by 
Analysis
G Iii Apparel (GIII) EBITDA (2010 - 2026) Analysis & Trends
On a TTM basis, G Iii Apparel's EBITDA came in at $209.78 million as of Jul 31, 2026, down 27.7% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $137 million, down 57.3% from FY2025.
- Annual EBITDA has a five-year compound annual growth rate of 2.4% (FY2021 to FY2026).
- Across earlier fiscal years, EBITDA came in at $320.52 million in FY2025 (+3.1%), $310.87 million in FY2024, -$81.7 million in FY2023 and $338.72 million in FY2022 (+178.9%).
- Quarterly EBITDA has ranged from -$284.73 million in fiscal Q4 2023 to $196.88 million in fiscal Q3 2024 over the past five years.
- On a year-over-year basis, EBITDA rose in two of the last seven quarters, with growth averaging 59.0%.
- Peak year-over-year performance for EBITDA in the last five years was growth of 514.1% in fiscal Q1 2027, against a decline of 64.0% in fiscal Q1 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $92.42 million (Q1 2027), -$21.17 million (Q4 2026) and $119.5 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 53.94 Bn | 19.93 Bn | 5.39 Bn | 1.50 Bn |
| 2 | Tapestry | 22.74 Bn | 18.69 Bn | 1.56 Bn | 500.90 Mn |
| 3 | Ralph Lauren | 21.47 Bn | 13.57 Bn | 1.44 Bn | 401.30 Mn |
| 4 | Deckers Outdoor | 11.15 Bn | 4.02 Bn | - | - |
| 5 | Lululemon Athletica | 10.72 Bn | 4.97 Bn | 1.46 Bn | 595.99 Mn |
| 6 | Levi Strauss | 7.64 Bn | 4.29 Bn | 979.10 Mn | 179.40 Mn |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn | 244.22 Mn |
| 8 | Birkenstock Holding | 6.06 Bn | 4.37 Bn | 493.89 Mn | 244.59 Mn |
| 9 | Crocs | 5.89 Bn | 5.30 Bn | 700.71 Mn | 305.72 Mn |
| 10 | G Iii Apparel | 1.16 Bn | -350.90 Mn | 250.38 Mn | 19.03 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 19.03 Mn |
| Apr 30, 2026 | 92.42 Mn |
| Jan 31, 2026 | -21.17 Mn |
| Oct 31, 2025 | 119.50 Mn |
| Jul 31, 2025 | 23.63 Mn |
| Apr 30, 2025 | 15.05 Mn |
| Jan 31, 2025 | 78.51 Mn |
| Oct 31, 2024 | 172.89 Mn |
| Jul 31, 2024 | 46.84 Mn |
| Apr 30, 2024 | 22.27 Mn |
| Jan 31, 2024 | 54.70 Mn |
| Oct 31, 2023 | 196.88 Mn |
| Jul 31, 2023 | 37.45 Mn |
| Apr 30, 2023 | 21.84 Mn |
| Jan 31, 2023 | -284.73 Mn |
| Oct 31, 2022 | 104.48 Mn |
| Jul 31, 2022 | 37.91 Mn |
| Apr 30, 2022 | 60.63 Mn |
| Jan 31, 2022 | 73.67 Mn |
| Oct 31, 2021 | 165.15 Mn |
API Access
G Iii Apparel EBITDA 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=ebitda&ticker=GIII&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "GIII", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=GIII&period=max&api_key=YOUR_API_KEY");
const data = await res.json();