Alamo (ALG) Operating Expenses (2010 - 2026)
Alamo (ALG) recorded Operating Expenses of $60.08 million in Q2 2026, up 5.1% from $57.14 million a year earlier and up 4.0% from the prior quarter.
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Analysis
Alamo (ALG) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Alamo's Operating Expenses came in at $236.03 million as of Jun 30, 2026, up 6.6% year-over-year; for FY2025, it was $229.66 million, down 0.8% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 4.5% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $231.45 million in FY2024 (-3.6%), $240.16 million in FY2023 (+12.9%), $212.65 million in FY2022 (+4.8%) and $202.94 million in FY2021 (+10.2%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q2 2024.
- On a year-over-year basis, Operating Expenses has increased for four consecutive quarters, with an average decline of 0.9% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 19.3% in Q3 2021, against a decline of 11.3% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $57.77 million (Q1 2026), $58.26 million (Q4 2025) and $59.93 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 380.10 Bn | 351.79 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 208.03 Bn | 202.73 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 183.47 Bn | 192.23 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 168.26 Bn | 165.49 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 122.34 Bn | 120.47 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 95.63 Bn | 86.25 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 87.72 Bn | 80.47 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 86.87 Bn | 68.33 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 76.08 Bn | 72.64 Bn | 1.90 Bn | - |
| 10 | Alamo | 1.92 Bn | 979.51 Mn | 110.86 Mn | 60.08 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 60.08 Mn |
| Mar 31, 2026 | 57.77 Mn |
| Dec 31, 2025 | 58.26 Mn |
| Sep 30, 2025 | 59.93 Mn |
| Jun 30, 2025 | 57.14 Mn |
| Mar 31, 2025 | 54.33 Mn |
| Dec 31, 2024 | 53.30 Mn |
| Sep 30, 2024 | 56.75 Mn |
| Jun 30, 2024 | 60.82 Mn |
| Mar 31, 2024 | 60.59 Mn |
| Dec 31, 2023 | 60.07 Mn |
| Sep 30, 2023 | 60.56 Mn |
| Jun 30, 2023 | 59.86 Mn |
| Mar 31, 2023 | 59.67 Mn |
| Dec 31, 2022 | 51.28 Mn |
| Sep 30, 2022 | 52.72 Mn |
| Jun 30, 2022 | 55.01 Mn |
| Mar 31, 2022 | 53.64 Mn |
| Dec 31, 2021 | 52.14 Mn |
| Sep 30, 2021 | 52.59 Mn |
API Access
Alamo 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=ALG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ALG", "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=ALG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();