Canada Goose Holdings (GOOS) Operating Expenses (2016 - 2026)
Canada Goose Holdings (GOOS) recorded Operating Expenses of $186.85 million in fiscal Q4 2026 (quarter ended Mar 29, 2026), up 22.3% from $152.82 million a year earlier but down 64.1% from the prior quarter.
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Analysis
Canada Goose Holdings (GOOS) Operating Expenses (2016 - 2026) Analysis & Trends
For FY2026 (ended Mar 29, 2026), Canada Goose Holdings reported Operating Expenses of $706.79 million, up 26.1% from FY2025.
- Annual Operating Expenses has a five-year compound annual growth rate of 16.4% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $560.44 million in FY2025 (-4.7%), $588.14 million in FY2024 (+413.3%), $114.58 million in FY2023 (+16.2%) and $98.61 million in FY2022 (-70.2%).
- Quarterly Operating Expenses has ranged from $104.24 million in fiscal Q3 2022 to $520.28 million in fiscal Q3 2026 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for three consecutive quarters, with growth averaging 18.1% over the last seven quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 249.8% in fiscal Q3 2023, against a decline of 46.8% in fiscal Q3 2022 at the low end.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 56.35 Bn | 22.56 Bn | 4.80 Bn | 3.91 Bn |
| 2 | Tapestry | 23.94 Bn | 19.90 Bn | 1.56 Bn | 1.12 Bn |
| 3 | Ralph Lauren | 22.75 Bn | 14.85 Bn | 1.44 Bn | 1.10 Bn |
| 4 | Deckers Outdoor | 12.63 Bn | 5.50 Bn | - | - |
| 5 | Lululemon Athletica | 11.24 Bn | 5.49 Bn | 1.46 Bn | 1.01 Bn |
| 6 | Levi Strauss | 8.01 Bn | 4.59 Bn | 1.07 Bn | 843.50 Mn |
| 7 | V F | 6.82 Bn | 3.44 Bn | 917.04 Mn | 1.75 Bn |
| 8 | Gildan Activewear | 6.57 Bn | 5.49 Bn | 459.76 Mn | 283.86 Mn |
| 9 | Birkenstock Holding | 6.11 Bn | 4.44 Bn | 493.89 Mn | 37.80 Mn |
| 10 | Canada Goose Holdings | 793.40 Mn | 31.71 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 29, 2026 | 186.85 Mn |
| Dec 28, 2025 | 520.28 Mn |
| Sep 28, 2025 | 299.92 Mn |
| Mar 30, 2025 | 152.82 Mn |
| Dec 29, 2024 | 401.01 Mn |
| Sep 29, 2024 | 228.68 Mn |
| Jun 30, 2024 | 118.81 Mn |
| Mar 31, 2024 | 110.95 Mn |
| Dec 31, 2023 | 428.23 Mn |
| Oct 1, 2023 | 247.68 Mn |
| Mar 31, 2023 | 114.58 Mn |
| Jan 1, 2023 | 364.64 Mn |
| Oct 2, 2022 | 206.33 Mn |
| Mar 31, 2022 | 98.61 Mn |
| Jan 2, 2022 | 336.23 Mn |
| Sep 26, 2021 | 170.91 Mn |
| Mar 28, 2021 | 103.73 Mn |
| Dec 27, 2020 | 195.78 Mn |
| Sep 27, 2020 | 83.28 Mn |
| Mar 29, 2020 | 72.04 Mn |
API Access
Canada Goose Holdings Operating Expenses 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=operating-expenses&ticker=GOOS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GOOS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=GOOS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();