Acco Brands (ACCO) Operating Expenses (2010 - 2026)
Acco Brands' Operating Expenses came in at $103.8 million for Q2 2026, up 7.3% from $96.7 million a year earlier but down 11.4% from the prior quarter.
Acco Brands (ACCO) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Acco Brands reported Operating Expenses of $425.7 million, down 0.3% year-over-year; for FY2025, it was $407.7 million, down 31.2% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 1.4% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $592.4 million in FY2024 (+7.0%), $553.6 million in FY2023 (+7.0%), $517.5 million in FY2022 (+11.6%) and $463.9 million in FY2021 (+22.1%).
- The five-year range for quarterly Operating Expenses is $94.6 million (Q2 2022) to $263.8 million (Q2 2024).
- Year-over-year, Operating Expenses increased in two of the last seven quarters, with an average decline of 16.3%.
- The fastest year-over-year change in Operating Expenses over five years came in Q2 2024 (growth of 142.0%), and the weakest in Q2 2025 (a decline of 63.3%).
- Business Quant data shows ACCO's Operating Expenses at $117.2 million (Q1 2026), $104.1 million (Q4 2025) and $100.6 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amer Sports | 15.22 Bn | 11.27 Bn | 1.07 Bn | -909.20 Mn |
| 2 | Hasbro | 12.37 Bn | 8.16 Bn | 867.20 Mn | 887.10 Mn |
| 3 | Acushnet Holdings | 4.82 Bn | 4.56 Bn | 445.83 Mn | 267.00 Mn |
| 4 | Mattel | 3.62 Bn | 292.28 Mn | 542.12 Mn | - |
| 5 | YETI Holdings | 2.99 Bn | 2.31 Bn | 322.52 Mn | 229.01 Mn |
| 6 | Callaway Golf | 2.52 Bn | -29.40 Mn | 306.70 Mn | 191.90 Mn |
| 7 | Peloton Interactive | 2.19 Bn | -2.43 Bn | 344.40 Mn | 263.20 Mn |
| 8 | Unusual Machines | 1.22 Bn | 760.93 Mn | 5.80 Mn | 13.64 Mn |
| 9 | Sturm Ruger | 679.08 Mn | 283.08 Mn | 33.74 Mn | 26.11 Mn |
| 10 | Acco Brands | 387.69 Mn | 15.49 Mn | 134.10 Mn | 103.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 103.80 Mn |
| Mar 31, 2026 | 117.20 Mn |
| Dec 31, 2025 | 104.10 Mn |
| Sep 30, 2025 | 100.60 Mn |
| Jun 30, 2025 | 96.70 Mn |
| Mar 31, 2025 | 106.30 Mn |
| Dec 31, 2024 | 113.50 Mn |
| Sep 30, 2024 | 110.60 Mn |
| Jun 30, 2024 | 263.80 Mn |
| Dec 31, 2023 | 222.80 Mn |
| Sep 30, 2023 | 112.60 Mn |
| Jun 30, 2023 | 109.00 Mn |
| Dec 31, 2022 | 109.70 Mn |
| Sep 30, 2022 | 200.40 Mn |
| Jun 30, 2022 | 94.60 Mn |
| Mar 31, 2022 | 112.80 Mn |
| Dec 31, 2021 | 114.50 Mn |
| Sep 30, 2021 | 118.60 Mn |
| Jun 30, 2021 | 114.20 Mn |
| Mar 31, 2021 | 116.60 Mn |
Acco Brands 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=ACCO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ACCO", "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=ACCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();