Federal Home Loan Mortgage (FMCC) Long-Term Debt (2010 - 2026)
Federal Home Loan Mortgage (FMCC) recorded Non-Current Debt of $2 trillion in Q3 2016, up 2.7% from $1.95 trillion a year earlier and up 1.4% from the prior quarter.
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Analysis
Federal Home Loan Mortgage (FMCC) Long-Term Debt (2010 - 2026) Analysis & Trends
At the end of FY2015, Federal Home Loan Mortgage reported Non-Current Debt of $1.97 trillion, up 2.1% from FY2014.
- Annual Non-Current Debt has a five-year compound annual growth rate of -2.6% (FY2010 to FY2015).
- Across earlier years, Non-Current Debt came in at $1.93 trillion in FY2014 (-0.6%), $1.94 trillion in FY2013 (-1.3%), $1.97 trillion in FY2012 (-7.7%) and $2.13 trillion in FY2011 (-4.9%).
- The Q3 2016 figure is the highest quarterly Non-Current Debt since Q2 2012.
- On a year-over-year basis, Non-Current Debt has increased for seven consecutive quarters, with growth averaging 1.7% over the last eight quarters.
- Peak year-over-year performance for Non-Current Debt in the last five years was growth of 2.7% in Q3 2016, against a decline of 7.7% in Q4 2012 at the low end.
- Per Business Quant, the preceding three quarters came in at $1.97 trillion (Q2 2016), $1.96 trillion (Q1 2016) and $1.97 trillion (Q4 2015).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Long-Term Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | Royalty Pharma | 39.80 Bn | 40.13 Bn | - | 8.59 Bn |
| 2 | Rocket Companies | 38.90 Bn | 27.72 Bn | - | - |
| 3 | Orix | 38.66 Bn | 9.30 Bn | 13.83 Bn | 35.20 Bn |
| 4 | Federal National Mortgage Association Fannie Mae | 26.46 Bn | -16,107.65 Bn | - | - |
| 5 | Synchrony Financial | 22.47 Bn | -45.15 Bn | - | 17.03 Bn |
| 6 | Affirm Holdings | 22.07 Bn | 15.11 Bn | - | - |
| 7 | Royal Gold | 21.71 Bn | 20.92 Bn | 402.46 Mn | - |
| 8 | Ares Capital | 13.84 Bn | 11.59 Bn | - | 15.12 Bn |
| 9 | Annaly Capital Management | 13.83 Bn | 4.86 Bn | - | - |
| 10 | Federal Home Loan Mortgage | 12.64 Bn | -328.33 Bn | - | 157.00 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 157.00 Bn |
| Jun 30, 2026 | 163.75 Bn |
| Mar 31, 2026 | 169.85 Bn |
| Dec 31, 2025 | 169.30 Bn |
| Sep 30, 2025 | 46.00 Mn |
| Jun 30, 2025 | 31.00 Mn |
| Mar 31, 2025 | 11.00 Mn |
| Dec 31, 2024 | 167.33 Bn |
| Sep 30, 2024 | 3,265.27 Bn |
| Jun 30, 2024 | 3,227.61 Bn |
| Mar 31, 2024 | 3,211.74 Bn |
| Dec 31, 2023 | 30.00 Mn |
| Sep 30, 2023 | 3,202.10 Bn |
| Jun 30, 2023 | 3,189.09 Bn |
| Mar 31, 2023 | 3,167.51 Bn |
| Dec 31, 2022 | 3.86 Bn |
| Sep 30, 2022 | 3,137.22 Bn |
| Jun 30, 2022 | 3,093.18 Bn |
| Mar 31, 2022 | 3,059.13 Bn |
| Dec 31, 2021 | 3,208.35 Bn |
API Access
Federal Home Loan Mortgage Long-Term Debt 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=long-term-debt&ticker=FMCC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt", "ticker": "FMCC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=long-term-debt&ticker=FMCC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();