Argan (AGX) Operating Expenses (2010 - 2026)
Argan's Operating Expenses was $17.41 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), up 22.5% from $14.21 million a year earlier and up 10.8% from the prior quarter.
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Analysis
Argan (AGX) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Argan's Operating Expenses was $65.38 million through Jul 31, 2026, up 17.4% year-over-year; for FY2026 (ended Jan 31, 2026), it was $58.98 million, up 11.7% from FY2025.
- Operating Expenses shows a five-year compound annual growth rate of 8.6% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $52.79 million in FY2025 (+19.0%), $44.38 million in FY2024 (-0.7%), $44.69 million in FY2023 (-5.6%) and $47.32 million in FY2022 (+21.2%).
- Quarterly Operating Expenses has moved between $10.47 million (fiscal Q4 2023) and $17.93 million (fiscal Q4 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for 11 straight quarters, with growth averaging 17.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q4 2022 (growth of 51.8%); the worst was fiscal Q4 2023 (a decline of 32.5%).
- Per Business Quant data, AGX's Operating Expenses in the three fiscal quarters before Q2 2027 was $15.72 million (Q1 2027), $17.93 million (Q4 2026) and $14.32 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Quanta Services | 102.72 Bn | 100.91 Bn | 1.55 Bn | 698.49 Mn |
| 2 | Ferrovial | 37.36 Bn | 17.95 Bn | - | - |
| 3 | Emcor | 34.45 Bn | 30.84 Bn | 1.02 Bn | 475.04 Mn |
| 4 | Mastec | 17.62 Bn | 16.52 Bn | 556.28 Mn | 292.57 Mn |
| 5 | Jacobs Solutions | 16.24 Bn | 10.89 Bn | 810.70 Mn | 524.00 Mn |
| 6 | Sterling Infrastructure | 16.06 Bn | 14.42 Bn | 289.96 Mn | 65.66 Mn |
| 7 | IES Holdings | 13.53 Bn | 12.40 Bn | 340.66 Mn | 162.17 Mn |
| 8 | Dycom Industries | 8.22 Bn | 7.36 Bn | - | - |
| 9 | Aecom | 7.69 Bn | 3.02 Bn | -34.04 Mn | 46.45 Mn |
| 10 | Argan | 5.45 Bn | 3.45 Bn | 74.22 Mn | 17.41 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 17.41 Mn |
| Apr 30, 2026 | 15.72 Mn |
| Jan 31, 2026 | 17.93 Mn |
| Oct 31, 2025 | 14.32 Mn |
| Jul 31, 2025 | 14.21 Mn |
| Apr 30, 2025 | 12.52 Mn |
| Jan 31, 2025 | 14.95 Mn |
| Oct 31, 2024 | 14.00 Mn |
| Jul 31, 2024 | 12.43 Mn |
| Apr 30, 2024 | 11.43 Mn |
| Jan 31, 2024 | 11.91 Mn |
| Oct 31, 2023 | 11.38 Mn |
| Jul 31, 2023 | 10.50 Mn |
| Apr 30, 2023 | 10.59 Mn |
| Jan 31, 2023 | 10.47 Mn |
| Oct 31, 2022 | 12.67 Mn |
| Jul 31, 2022 | 10.98 Mn |
| Apr 30, 2022 | 10.58 Mn |
| Jan 31, 2022 | 15.51 Mn |
| Oct 31, 2021 | 11.59 Mn |
API Access
Argan 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=AGX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AGX", "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=AGX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();