G Iii Apparel (GIII) Inventory (2010 - 2026)
G Iii Apparel (GIII) recorded Inventory of $555.02 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), down 13.2% from $639.76 million a year earlier but up 32.8% from the prior quarter.
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Analysis
G Iii Apparel (GIII) Inventory (2010 - 2026) Analysis & Trends
At the end of FY2026 (ended Jan 31, 2026), G Iii Apparel reported Inventory of $460.03 million, down 3.8% from FY2025.
- Annual Inventory has declined for three straight fiscal years, though with a five-year compound annual growth rate of 2.0% (FY2021 to FY2026).
- Across earlier fiscal years, Inventory came in at $478.09 million in FY2025 (-8.1%), $520.43 million in FY2024 (-26.6%), $709.35 million in FY2023 (+38.5%) and $512.16 million in FY2022 (+23.0%).
- Quarterly Inventory has ranged from $417.86 million in fiscal Q1 2027 to $1.04 billion in fiscal Q2 2023 over the past five years.
- On a year-over-year basis, Inventory has declined for three consecutive quarters, with an average decline of 5.1% over the last eight quarters.
- Peak year-over-year performance for Inventory in the last five years was growth of 108.4% in fiscal Q2 2023, against a decline of 34.3% in fiscal Q3 2024 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $417.86 million (Q1 2027), $460.03 million (Q4 2026) and $547.09 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 53.94 Bn | 19.93 Bn | 5.39 Bn | - |
| 2 | Tapestry | 22.74 Bn | 18.69 Bn | 1.56 Bn | 826.20 Mn |
| 3 | Ralph Lauren | 21.47 Bn | 13.57 Bn | 1.44 Bn | 1.16 Bn |
| 4 | Deckers Outdoor | 11.15 Bn | 4.02 Bn | - | 487.02 Mn |
| 5 | Lululemon Athletica | 10.72 Bn | 4.97 Bn | 1.46 Bn | 1.71 Bn |
| 6 | Levi Strauss | 7.64 Bn | 4.29 Bn | 979.10 Mn | 1.16 Bn |
| 7 | Gildan Activewear | 6.52 Bn | 5.51 Bn | 459.76 Mn | 2.17 Bn |
| 8 | Birkenstock Holding | 6.06 Bn | 4.37 Bn | 493.89 Mn | 980.27 Mn |
| 9 | Crocs | 5.89 Bn | 5.30 Bn | 700.71 Mn | 389.21 Mn |
| 10 | G Iii Apparel | 1.16 Bn | -350.90 Mn | 250.38 Mn | 555.02 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 555.02 Mn |
| Apr 30, 2026 | 417.86 Mn |
| Jan 31, 2026 | 460.03 Mn |
| Oct 31, 2025 | 547.09 Mn |
| Jul 31, 2025 | 639.76 Mn |
| Apr 30, 2025 | 456.48 Mn |
| Jan 31, 2025 | 478.09 Mn |
| Oct 31, 2024 | 532.46 Mn |
| Jul 31, 2024 | 610.49 Mn |
| Apr 30, 2024 | 479.67 Mn |
| Jan 31, 2024 | 520.43 Mn |
| Oct 31, 2023 | 591.53 Mn |
| Jul 31, 2023 | 804.86 Mn |
| Apr 30, 2023 | 630.31 Mn |
| Jan 31, 2023 | 709.35 Mn |
| Oct 31, 2022 | 900.99 Mn |
| Jul 31, 2022 | 1.04 Bn |
| Apr 30, 2022 | 550.06 Mn |
| Jan 31, 2022 | 512.16 Mn |
| Oct 31, 2021 | 448.99 Mn |
API Access
G Iii Apparel Inventory 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=inventory&ticker=GIII&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "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=inventory&ticker=GIII&period=max&api_key=YOUR_API_KEY");
const data = await res.json();