Great Elm Capital (GECC) Total Liabilities (2016 - 2026)
Great Elm Capital's Total Liabilities came in at $153.99 million for Q3 2026, down 45.0% from $279.95 million a year earlier and down 9.2% from the prior quarter.
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Analysis
Great Elm Capital (GECC) Total Liabilities (2016 - 2026) Analysis & Trends
At the end of FY2025, Great Elm Capital's Total Liabilities was $227.83 million, up 10.6% from FY2024.
- Total Liabilities carries a four-year compound annual growth rate of -10.3% (FY2021 to FY2025).
- Going back by year, Total Liabilities was $205.92 million in FY2024 (+39.1%), $148.09 million in FY2023 (-34.3%), $225.3 million in FY2022 (-35.9%) and $351.76 million in FY2021.
- The Q3 2026 figure represents the lowest quarterly Total Liabilities since Q4 2023.
- Year-over-year, Total Liabilities has declined for three consecutive quarters, with growth averaging 1.4% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q3 2024 (growth of 103.0%), and the weakest in Q3 2026 (a decline of 45.0%).
- Business Quant data shows GECC's Total Liabilities at $169.56 million (Q2 2026), $175.29 million (Q1 2026) and $227.83 million (Q4 2025) in the three quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Rocket Companies | 41.00 Bn | 29.82 Bn | - | 35.84 Bn |
| 2 | Royalty Pharma | 39.88 Bn | 40.21 Bn | - | 9.67 Bn |
| 3 | Orix | 36.75 Bn | 7.39 Bn | 13.83 Bn | 66.29 Bn |
| 4 | Federal National Mortgage Association Fannie Mae | 25.40 Bn | -16,108.71 Bn | - | 4,198.25 Bn |
| 5 | Royal Gold | 23.20 Bn | 22.41 Bn | 402.46 Mn | 1.59 Bn |
| 6 | Affirm Holdings | 22.35 Bn | 15.40 Bn | - | 10.73 Bn |
| 7 | Synchrony Financial | 22.29 Bn | -45.34 Bn | - | 105.92 Bn |
| 8 | Annaly Capital Management | 14.69 Bn | 5.72 Bn | - | 130.25 Bn |
| 9 | Ares Capital | 14.04 Bn | 11.79 Bn | - | 16.65 Bn |
| 10 | Great Elm Capital | 69.59 Mn | 65.12 Mn | - | 153.99 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 153.99 Mn |
| Jun 30, 2026 | 169.56 Mn |
| Mar 31, 2026 | 175.29 Mn |
| Dec 31, 2025 | 227.83 Mn |
| Sep 30, 2025 | 279.95 Mn |
| Jun 30, 2025 | 269.29 Mn |
| Mar 31, 2025 | 218.54 Mn |
| Dec 31, 2024 | 205.92 Mn |
| Sep 30, 2024 | 301.20 Mn |
| Jun 30, 2024 | 200.51 Mn |
| Mar 31, 2024 | 160.33 Mn |
| Dec 31, 2023 | 148.09 Mn |
| Sep 30, 2023 | 148.38 Mn |
| Jun 30, 2023 | 229.63 Mn |
| Mar 31, 2023 | 223.76 Mn |
| Dec 31, 2022 | 225.30 Mn |
| Sep 30, 2022 | 197.61 Mn |
| Jun 30, 2022 | 248.89 Mn |
| Mar 31, 2022 | 246.49 Mn |
| Dec 31, 2021 | 351.76 Mn |
API Access
Great Elm Capital 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=GECC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "GECC", "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=GECC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();