Acacia Research (ACTG) Operating Expenses (2010 - 2026)
Acacia Research's Operating Expenses was $106.05 million in Q2 2026, up 66.7% from $63.62 million a year earlier and up 69.4% from the prior quarter.
Acacia Research (ACTG) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Acacia Research's Operating Expenses was $297.73 million through Jun 30, 2026, up 20.1% year-over-year; for FY2025, it came in at $278.82 million, up 79.6% from FY2024.
- Operating Expenses has now increased for six consecutive years, with a five-year compound annual growth rate of 41.4% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $155.24 million in FY2024 (+49.0%), $104.17 million in FY2023 (+4.9%), $99.32 million in FY2022 (+35.1%) and $73.5 million in FY2021 (+49.1%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q4 2015.
- Compared with a year earlier, Operating Expenses was higher in six of the last eight quarters, with growth averaging 73.7%.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2021 (growth of 400.4%); the worst was Q1 2026 (a decline of 27.3%).
- Per Business Quant data, ACTG's Operating Expenses in the three quarters before Q2 2026 was $62.6 million (Q1 2026), $63.21 million (Q4 2025) and $65.87 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | BlackRock | 174.92 Bn | 121.05 Bn | - | 4.62 Bn |
| 2 | Spdr Gold Trust | 136.71 Bn | -421.29 Bn | - | 149.76 Mn |
| 3 | Blackstone | 88.22 Bn | 78.20 Bn | - | 2.38 Bn |
| 4 | Brookfield | 83.92 Bn | -99.40 Bn | - | 14.94 Bn |
| 5 | Kkr | 79.85 Bn | -3.72 Mn | - | 5.41 Bn |
| 6 | Brookfield Asset Management | 73.42 Bn | 68.22 Bn | - | 659.00 Mn |
| 7 | Apollo Global Management | 65.92 Bn | -16.87 Bn | 10.56 Bn | 8.74 Bn |
| 8 | Wheaton Precious Metals | 59.50 Bn | 54.92 Bn | 687.86 Mn | 133.83 Mn |
| 9 | Franco Nevada | 46.38 Bn | 43.74 Bn | 451.00 Mn | 5.30 Mn |
| 10 | Acacia Research | 407.75 Mn | -893.96 Mn | 30.65 Mn | 106.05 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 106.05 Mn |
| Mar 31, 2026 | 62.60 Mn |
| Dec 31, 2025 | 63.21 Mn |
| Sep 30, 2025 | 65.87 Mn |
| Jun 30, 2025 | 63.62 Mn |
| Mar 31, 2025 | 86.12 Mn |
| Dec 31, 2024 | 64.65 Mn |
| Sep 30, 2024 | 33.58 Mn |
| Jun 30, 2024 | 30.60 Mn |
| Mar 31, 2024 | 26.41 Mn |
| Dec 31, 2023 | 36.37 Mn |
| Sep 30, 2023 | 23.24 Mn |
| Jun 30, 2023 | 20.43 Mn |
| Mar 31, 2023 | 24.13 Mn |
| Dec 31, 2022 | 27.67 Mn |
| Sep 30, 2022 | 27.24 Mn |
| Jun 30, 2022 | 22.39 Mn |
| Mar 31, 2022 | 22.02 Mn |
| Dec 31, 2021 | 31.96 Mn |
| Sep 30, 2021 | 14.30 Mn |
Acacia Research 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=ACTG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ACTG", "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=ACTG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();