Arq (ARQ) Operating Expenses (2012 - 2026)
Arq (ARQ) recorded Operating Expenses of $11.58 million in Q2 2026, up 2.4% from $11.31 million a year earlier and up 6.0% from the prior quarter.
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Analysis
Arq (ARQ) Operating Expenses (2012 - 2026) Analysis & Trends
On a TTM basis, Arq's Operating Expenses came in at $88.66 million as of Jun 30, 2026, up 114.4% year-over-year; for FY2025, it came in at $86.49 million, up 108.9% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -4.4% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $41.4 million in FY2024 (-8.4%), $45.2 million in FY2023 (-60.7%), $115.06 million in FY2022 (+20.5%) and $95.44 million in FY2021 (-11.9%).
- Quarterly Operating Expenses has ranged from $9.25 million in Q1 2025 to $55.22 million in Q4 2025 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for three consecutive quarters, with growth averaging 61.3% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 488.0% in Q4 2025, against a decline of 62.5% in Q3 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $10.92 million (Q1 2026), $55.22 million (Q4 2025) and $10.95 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Linde | 235.27 Bn | 218.38 Bn | 4.43 Bn | 928.00 Mn |
| 2 | Corning | 106.79 Bn | 99.92 Bn | 1.63 Bn | 907.00 Mn |
| 3 | Sherwin Williams | 83.92 Bn | 82.96 Bn | 3.34 Bn | 2.10 Bn |
| 4 | Air Products & Chemicals | 68.64 Bn | 66.53 Bn | 1.04 Bn | 3.15 Bn |
| 5 | LyondellBasell Industries | 42.22 Bn | 31.84 Bn | 2.04 Bn | 7.63 Bn |
| 6 | Nutrien | 33.30 Bn | 30.16 Bn | 3.25 Bn | 235.00 Mn |
| 7 | Ppg Industries | 25.14 Bn | 17.94 Bn | 1.81 Bn | 1.15 Bn |
| 8 | International Flavors & Fragrances | 23.95 Bn | 21.65 Bn | 853.00 Mn | 613.00 Mn |
| 9 | Dow | 22.98 Bn | 7.98 Bn | 2.17 Bn | 1.25 Bn |
| 10 | Arq | 75.91 Mn | 56.73 Mn | 11.51 Mn | 11.58 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 11.58 Mn |
| Mar 31, 2026 | 10.92 Mn |
| Dec 31, 2025 | 55.22 Mn |
| Sep 30, 2025 | 10.95 Mn |
| Jun 30, 2025 | 11.31 Mn |
| Mar 31, 2025 | 9.25 Mn |
| Dec 31, 2024 | 9.39 Mn |
| Sep 30, 2024 | 11.41 Mn |
| Jun 30, 2024 | 9.60 Mn |
| Mar 31, 2024 | 11.01 Mn |
| Dec 31, 2023 | 10.90 Mn |
| Sep 30, 2023 | 11.65 Mn |
| Jun 30, 2023 | 11.20 Mn |
| Mar 31, 2023 | 11.46 Mn |
| Dec 31, 2022 | 26.78 Mn |
| Sep 30, 2022 | 31.06 Mn |
| Jun 30, 2022 | 27.48 Mn |
| Mar 31, 2022 | 29.74 Mn |
| Dec 31, 2021 | 24.98 Mn |
| Sep 30, 2021 | 27.56 Mn |
API Access
Arq 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=ARQ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ARQ", "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=ARQ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();