Agco (AGCO) Operating Expenses (2009 - 2026)
Agco's Operating Expenses was $346.9 million in Q2 2026, up 1.4% from $342 million a year earlier but down 0.6% from the prior quarter.
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Analysis
Agco (AGCO) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Agco's Operating Expenses was $1.41 billion through Jun 30, 2026, down 5.6% year-over-year; for FY2025, it was $1.39 billion, down 11.4% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 0.4% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.57 billion in FY2024 (+7.1%), $1.47 billion in FY2023 (-10.6%), $1.64 billion in FY2022 (+8.6%) and $1.51 billion in FY2021 (+10.7%).
- Quarterly Operating Expenses has moved between $338.8 million (Q1 2025) and $496 million (Q3 2023) over five years.
- Compared with a year earlier, Operating Expenses was higher in three of the last eight quarters, with an average decline of 7.3%.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2023 (growth of 26.1%); the worst was Q3 2024 (a decline of 28.5%).
- Per Business Quant data, AGCO's Operating Expenses in the three quarters before Q2 2026 was $349.1 million (Q1 2026), $361.2 million (Q4 2025) and $349.5 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 376.87 Bn | 348.57 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 208.65 Bn | 203.35 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 185.97 Bn | 194.73 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 167.50 Bn | 164.73 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 122.25 Bn | 120.39 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 93.95 Bn | 84.57 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 88.90 Bn | 81.65 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 87.39 Bn | 68.85 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 78.00 Bn | 74.56 Bn | 1.90 Bn | - |
| 10 | Agco | 8.23 Bn | 5.69 Bn | 645.90 Mn | 346.90 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 346.90 Mn |
| Mar 31, 2026 | 349.10 Mn |
| Dec 31, 2025 | 361.20 Mn |
| Sep 30, 2025 | 349.50 Mn |
| Jun 30, 2025 | 342.00 Mn |
| Mar 31, 2025 | 338.80 Mn |
| Dec 31, 2024 | 454.20 Mn |
| Sep 30, 2024 | 354.80 Mn |
| Jun 30, 2024 | 410.00 Mn |
| Mar 31, 2024 | 351.40 Mn |
| Dec 31, 2023 | 420.40 Mn |
| Sep 30, 2023 | 496.00 Mn |
| Jun 30, 2023 | 495.20 Mn |
| Mar 31, 2023 | 452.80 Mn |
| Dec 31, 2022 | 462.20 Mn |
| Sep 30, 2022 | 393.20 Mn |
| Jun 30, 2022 | 410.40 Mn |
| Mar 31, 2022 | 374.40 Mn |
| Dec 31, 2021 | 403.10 Mn |
| Sep 30, 2021 | 360.30 Mn |
API Access
Agco 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=AGCO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AGCO", "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=AGCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();