Graham (GHM) EBITDA (2010 - 2026)
Graham (GHM) recorded EBITDA of $6.87 million in fiscal Q1 2027 (quarter ended Jun 30, 2026), up 5.9% from $6.49 million a year earlier and up 29.1% from the prior quarter.
Powered by 
Analysis
Graham (GHM) EBITDA (2010 - 2026) Analysis & Trends
On a TTM basis, Graham's EBITDA came in at $23.25 million as of Jun 30, 2026, up 1.2% year-over-year; for FY2026 (ended Mar 31, 2026), it came in at $22.86 million, up 8.2% from FY2025.
- Annual EBITDA has increased for three straight fiscal years, with a five-year compound annual growth rate of 35.8% (FY2021 to FY2026).
- Across earlier fiscal years, EBITDA came in at $21.12 million in FY2025 (+71.0%), $12.35 million in FY2024 (+70.7%), $7.24 million in FY2023 and -$5.74 million in FY2022.
- The fiscal Q1 2027 figure is the highest quarterly EBITDA since fiscal Q4 2025.
- On a year-over-year basis, EBITDA rose in seven of the last eight quarters, with growth averaging 54.3%.
- Peak year-over-year performance for EBITDA in the last five years was growth of 182.1% in fiscal Q2 2025, against a decline of 77.4% in fiscal Q2 2022 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $5.32 million (Q4 2026), $5.13 million (Q3 2026) and $5.92 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 376.87 Bn | 348.57 Bn | 7.76 Bn | 4.91 Bn |
| 2 | Amphenol | 208.65 Bn | 203.35 Bn | 3.55 Bn | 2.93 Bn |
| 3 | Deere | 185.97 Bn | 194.73 Bn | 4.66 Bn | 2.46 Bn |
| 4 | Eaton | 167.50 Bn | 164.73 Bn | 2.86 Bn | 1.79 Bn |
| 5 | Parker-Hannifin | 122.25 Bn | 120.39 Bn | 2.25 Bn | 1.61 Bn |
| 6 | Vertiv Holdings | 93.95 Bn | 84.57 Bn | 1.23 Bn | 753.70 Mn |
| 7 | Emerson Electric | 88.90 Bn | 81.65 Bn | 2.66 Bn | 1.69 Bn |
| 8 | 3M | 87.39 Bn | 68.85 Bn | 2.68 Bn | 1.32 Bn |
| 9 | Illinois Tool Works | 78.00 Bn | 74.56 Bn | 1.90 Bn | 1.25 Bn |
| 10 | Graham | 1.02 Bn | 946.23 Mn | 17.80 Mn | 6.87 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.87 Mn |
| Mar 31, 2026 | 5.32 Mn |
| Dec 31, 2025 | 5.13 Mn |
| Sep 30, 2025 | 5.92 Mn |
| Jun 30, 2025 | 6.49 Mn |
| Mar 31, 2025 | 7.08 Mn |
| Dec 31, 2024 | 3.76 Mn |
| Sep 30, 2024 | 5.65 Mn |
| Jun 30, 2024 | 4.64 Mn |
| Mar 31, 2024 | 3.09 Mn |
| Dec 31, 2023 | 2.33 Mn |
| Sep 30, 2023 | 2.00 Mn |
| Jun 30, 2023 | 4.92 Mn |
| Mar 31, 2023 | 1.17 Mn |
| Dec 31, 2022 | 2.18 Mn |
| Sep 30, 2022 | 1.44 Mn |
| Jun 30, 2022 | 2.46 Mn |
| Mar 31, 2022 | -448,000.00 |
| Dec 31, 2021 | -2.99 Mn |
| Sep 30, 2021 | 886,000.00 |
API Access
Graham EBITDA 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=ebitda&ticker=GHM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=GHM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();