Great Elm (GEG) Operating Expenses (2019 - 2026)
Great Elm's Operating Expenses was $6.16 million in fiscal Q4 2026 (quarter ended Jun 30, 2026), down 13.1% from $7.08 million a year earlier and down 16.7% from the prior quarter.
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Analysis
Great Elm (GEG) Operating Expenses (2019 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Operating Expenses at Great Elm came in at $28.54 million, up 22.8% from FY2025.
- Operating Expenses has now increased for four consecutive fiscal years, though with a five-year compound annual growth rate of -15.1% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $23.24 million in FY2025 (+15.3%), $20.15 million in FY2024 (+1.4%), $19.87 million in FY2023 (+49.9%) and $13.26 million in FY2022 (-79.5%).
- The fiscal Q4 2026 figure marks the lowest quarterly Operating Expenses since fiscal Q3 2025.
- Compared with a year earlier, Operating Expenses was higher in six of the last eight quarters, with growth averaging 20.9%.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q4 2023 (growth of 92.4%); the worst was fiscal Q2 2022 (a decline of 79.2%).
- Per Business Quant data, GEG's Operating Expenses in the three fiscal quarters before Q4 2026 was $7.39 million (Q3 2026), $7.23 million (Q2 2026) and $7.77 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | BlackRock | 164.03 Bn | 110.39 Bn | - | 4.62 Bn |
| 2 | Spdr Gold Trust | 134.08 Bn | -423.92 Bn | - | 149.76 Mn |
| 3 | Blackstone | 84.38 Bn | 79.31 Bn | - | 2.38 Bn |
| 4 | Brookfield | 81.99 Bn | -83.40 Bn | 4.47 Bn | 14.94 Bn |
| 5 | Kkr | 81.98 Bn | 48.46 Bn | - | 5.41 Bn |
| 6 | Brookfield Asset Management | 71.20 Bn | 67.45 Bn | - | 659.00 Mn |
| 7 | Apollo Global Management | 66.86 Bn | 4.54 Bn | 10.56 Bn | 8.74 Bn |
| 8 | Wheaton Precious Metals | 60.68 Bn | 56.11 Bn | 687.86 Mn | 133.83 Mn |
| 9 | Franco Nevada | 45.90 Bn | 43.27 Bn | 451.00 Mn | 7.80 Mn |
| 10 | Great Elm | 64.02 Mn | -139.68 Mn | - | 6.16 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.16 Mn |
| Mar 31, 2026 | 7.39 Mn |
| Dec 31, 2025 | 7.23 Mn |
| Sep 30, 2025 | 7.77 Mn |
| Jun 30, 2025 | 7.08 Mn |
| Mar 31, 2025 | 5.78 Mn |
| Dec 31, 2024 | 5.03 Mn |
| Sep 30, 2024 | 5.35 Mn |
| Jun 30, 2024 | 5.22 Mn |
| Mar 31, 2024 | 4.66 Mn |
| Dec 31, 2023 | 5.52 Mn |
| Sep 30, 2023 | 4.76 Mn |
| Jun 30, 2023 | 6.62 Mn |
| Mar 31, 2023 | 4.77 Mn |
| Dec 31, 2022 | 4.67 Mn |
| Sep 30, 2022 | 3.82 Mn |
| Jun 30, 2022 | 3.44 Mn |
| Mar 31, 2022 | 3.31 Mn |
| Dec 31, 2021 | 3.59 Mn |
| Sep 30, 2021 | 15.54 Mn |
API Access
Great Elm 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=GEG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GEG", "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=GEG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();