A.K.A. Brands Holding (AKA) Other Operating Expenses (2020 - 2026)
A.K.A. Brands Holding (AKA) reported Other Operating Expenses of $69.17 million for Q2 2026, up 5.9% from $65.32 million a year earlier and up 19.9% from the prior quarter.
A.K.A. Brands Holding (AKA) Other Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, A.K.A. Brands Holding's Other Operating Expenses came in at $260.15 million, up 5.5% year-over-year; for FY2025, it came in at $251.95 million, up 6.5% from FY2024.
- Other Operating Expenses has a five-year compound annual growth rate of 27.0% (FY2020 to FY2025).
- By year, Other Operating Expenses came in at $236.56 million in FY2024 (-17.5%), $286.74 million in FY2023 (-29.5%), $406.59 million in FY2022 (+100.8%) and $202.47 million in FY2021 (+165.8%).
- Five-year quarterly Other Operating Expenses spans a low of $49.09 million in Q1 2024 and a high of $228.22 million in Q4 2022.
- Year over year, Other Operating Expenses has now increased in each of the last seven quarters, with growth averaging 0.3% over the last eight quarters.
- The high point for year-over-year Other Operating Expenses in five years was Q4 2022 (growth of 240.6%); the low point was Q4 2023 (a decline of 73.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $57.71 million (Q1 2026), $71.56 million (Q4 2025) and $61.72 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nike | 55.70 Bn | 21.90 Bn | 4.80 Bn |
| 2 | Tapestry | 23.51 Bn | 19.47 Bn | 1.56 Bn |
| 3 | Ralph Lauren | 22.86 Bn | 14.96 Bn | 1.44 Bn |
| 4 | Deckers Outdoor | 12.32 Bn | 5.19 Bn | - |
| 5 | Lululemon Athletica | 10.92 Bn | 5.17 Bn | 1.46 Bn |
| 6 | Levi Strauss | 8.09 Bn | 4.67 Bn | 1.07 Bn |
| 7 | V F | 6.73 Bn | 3.35 Bn | 917.04 Mn |
| 8 | Gildan Activewear | 6.45 Bn | 5.37 Bn | 459.76 Mn |
| 9 | Birkenstock Holding | 6.04 Bn | 4.36 Bn | 493.89 Mn |
| 10 | A.K.A. Brands Holding | 110.16 Mn | 32.54 Mn | 97.84 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 69.17 Mn |
| Mar 31, 2026 | 57.71 Mn |
| Dec 31, 2025 | 71.56 Mn |
| Sep 30, 2025 | 61.72 Mn |
| Jun 30, 2025 | 65.32 Mn |
| Mar 31, 2025 | 53.36 Mn |
| Dec 31, 2024 | 66.84 Mn |
| Sep 30, 2024 | 61.17 Mn |
| Jun 30, 2024 | 59.47 Mn |
| Mar 31, 2024 | 49.09 Mn |
| Dec 31, 2023 | 59.57 Mn |
| Sep 30, 2023 | 123.70 Mn |
| Jun 30, 2023 | 54.29 Mn |
| Mar 31, 2023 | 49.18 Mn |
| Dec 31, 2022 | 228.22 Mn |
| Sep 30, 2022 | 57.98 Mn |
| Jun 30, 2022 | 64.32 Mn |
| Mar 31, 2022 | 56.07 Mn |
| Dec 31, 2021 | 67.01 Mn |
| Sep 30, 2021 | 56.05 Mn |
A.K.A. Brands Holding Other 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=other-operating-expenses&ticker=AKA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "AKA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=AKA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();