Great Elm (GEG) Total Liabilities (2020 - 2026)
Great Elm's Total Liabilities came in at $72.88 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), down 0.5% from $73.27 million a year earlier but up 1.3% from the prior quarter.
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Analysis
Great Elm (GEG) Total Liabilities (2020 - 2026) Analysis & Trends
Going back to fiscal Q4 2020, Great Elm's Total Liabilities data covers 24 quarters.
- Total Liabilities carries a five-year compound annual growth rate of -7.8% (FY2021 to FY2026).
- Going back by fiscal year, Total Liabilities was $73.27 million in FY2025 (+4.3%), $70.25 million in FY2024 (-2.5%), $72.05 million in FY2023 (-43.7%) and $128.06 million in FY2022 (+17.4%).
- The five-year range for quarterly Total Liabilities is $65.68 million (fiscal Q1 2025) to $128.06 million (fiscal Q4 2022).
- Year-over-year, Total Liabilities increased in four of the last eight quarters, with growth averaging 1.2%.
- The fastest year-over-year change in Total Liabilities over five years came in fiscal Q1 2023 (growth of 18.6%), and the weakest in fiscal Q1 2024 (a decline of 45.8%).
- Business Quant data shows GEG's Total Liabilities at $71.94 million (Q3 2026), $75.8 million (Q2 2026) and $71.87 million (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | BlackRock | 164.03 Bn | 110.39 Bn | - | 118.04 Bn |
| 2 | Spdr Gold Trust | 134.08 Bn | -423.92 Bn | - | 45.42 Mn |
| 3 | Blackstone | 84.38 Bn | 79.31 Bn | - | 28.83 Bn |
| 4 | Brookfield | 81.99 Bn | -83.40 Bn | 4.47 Bn | 11.30 Bn |
| 5 | Kkr | 81.98 Bn | 48.46 Bn | - | 337.08 Bn |
| 6 | Brookfield Asset Management | 71.20 Bn | 67.45 Bn | - | 10.89 Bn |
| 7 | Apollo Global Management | 66.86 Bn | 4.54 Bn | 10.56 Bn | 452.57 Bn |
| 8 | Wheaton Precious Metals | 60.68 Bn | 56.11 Bn | 687.86 Mn | 2.47 Bn |
| 9 | Franco Nevada | 45.90 Bn | 43.27 Bn | 451.00 Mn | 681.50 Mn |
| 10 | Great Elm | 64.02 Mn | -139.68 Mn | - | 72.88 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 72.88 Mn |
| Mar 31, 2026 | 71.94 Mn |
| Dec 31, 2025 | 75.80 Mn |
| Sep 30, 2025 | 71.87 Mn |
| Jun 30, 2025 | 73.27 Mn |
| Mar 31, 2025 | 71.88 Mn |
| Dec 31, 2024 | 68.43 Mn |
| Sep 30, 2024 | 65.68 Mn |
| Jun 30, 2024 | 70.25 Mn |
| Mar 31, 2024 | 75.88 Mn |
| Dec 31, 2023 | 71.62 Mn |
| Sep 30, 2023 | 68.92 Mn |
| Jun 30, 2023 | 72.05 Mn |
| Mar 31, 2023 | 68.93 Mn |
| Dec 31, 2022 | 110.57 Mn |
| Sep 30, 2022 | 127.25 Mn |
| Jun 30, 2022 | 128.06 Mn |
| Mar 31, 2022 | 92.75 Mn |
| Dec 31, 2021 | 106.44 Mn |
| Sep 30, 2021 | 107.33 Mn |
API Access
Great Elm Total Liabilities 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=total-liabilities&ticker=GEG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=GEG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();