Graham (GHM) Operating Expenses (2010 - 2026)
Graham (GHM) recorded Operating Expenses of $12.55 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), up 33.6% from $9.4 million a year earlier and up 2.5% from the prior quarter.
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Analysis
Graham (GHM) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Graham's Operating Expenses came in at $44.72 million as of Jun 30, 2026, up 18.6% year-over-year; for FY2026 (ended Mar 31, 2026), it was $41.56 million, up 11.9% from FY2025.
- Annual Operating Expenses has increased for six straight fiscal years, with a five-year compound annual growth rate of 18.9% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $37.14 million in FY2025 (+15.3%), $32.22 million in FY2024 (+39.7%), $23.06 million in FY2023 (+13.1%) and $20.39 million in FY2022 (+16.7%).
- The fiscal Q1 2027 figure is the highest quarterly Operating Expenses in data going back to fiscal Q1 2011.
- On a year-over-year basis, Operating Expenses has increased for five consecutive quarters, with growth averaging 16.2% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 59.5% in fiscal Q3 2024, against a decline of 4.2% in fiscal Q3 2022 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $12.25 million (Q4 2026), $10.13 million (Q3 2026) and $9.79 million (Q2 2026).
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 | Graham | 1.02 Bn | 946.23 Mn | 17.80 Mn | 12.55 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.55 Mn |
| Mar 31, 2026 | 12.25 Mn |
| Dec 31, 2025 | 10.13 Mn |
| Sep 30, 2025 | 9.79 Mn |
| Jun 30, 2025 | 9.40 Mn |
| Mar 31, 2025 | 10.32 Mn |
| Dec 31, 2024 | 9.26 Mn |
| Sep 30, 2024 | 8.72 Mn |
| Jun 30, 2024 | 8.84 Mn |
| Mar 31, 2024 | 10.65 Mn |
| Dec 31, 2023 | 8.43 Mn |
| Sep 30, 2023 | 6.12 Mn |
| Jun 30, 2023 | 7.02 Mn |
| Mar 31, 2023 | 7.24 Mn |
| Dec 31, 2022 | 5.28 Mn |
| Sep 30, 2022 | 5.06 Mn |
| Jun 30, 2022 | 5.49 Mn |
| Mar 31, 2022 | 5.85 Mn |
| Dec 31, 2021 | 4.73 Mn |
| Sep 30, 2021 | 4.97 Mn |
API Access
Graham 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=GHM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GHM", "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=GHM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();