Mfa Financial (MFA) Operating Expenses (2009 - 2026)
Mfa Financial (MFA) recorded Operating Expenses of $41.52 million in Q2 2026, up 5.6% from $39.31 million a year earlier but down 6.8% from the prior quarter.
Mfa Financial (MFA) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Mfa Financial's Operating Expenses came in at $160.19 million as of Jun 30, 2026, down 2.3% year-over-year; for FY2025, it was $155.06 million, down 9.0% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 1.8% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $170.41 million in FY2024 (+1.4%), $168 million in FY2023 (+1.9%), $164.81 million in FY2022 (+37.1%) and $120.19 million in FY2021 (-15.1%).
- Quarterly Operating Expenses has ranged from $33.46 million in Q3 2021 to $46.1 million in Q2 2022 over the past five years.
- On a year-over-year basis, Operating Expenses rose in two of the last eight quarters, with an average decline of 3.5%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 103.1% in Q4 2021, against a decline of 17.4% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $44.53 million (Q1 2026), $34.67 million (Q4 2025) and $39.47 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Rocket Companies | 43.90 Bn | 29.58 Bn | - | 2.50 Bn |
| 2 | Orix | 42.96 Bn | 43.46 Bn | - | 4.66 Bn |
| 3 | Royalty Pharma | 33.48 Bn | 33.39 Bn | - | 541.02 Mn |
| 4 | Federal National Mortgage Association Fannie Mae | 23.94 Bn | 23.94 Bn | - | 2.07 Bn |
| 5 | Affirm Holdings | 23.37 Bn | 17.06 Bn | - | 1.02 Bn |
| 6 | Synchrony Financial | 23.31 Bn | -44.66 Bn | - | 1.33 Bn |
| 7 | Royal Gold | 20.23 Bn | 19.45 Bn | 390.45 Mn | 173.18 Mn |
| 8 | Annaly Capital Management | 15.24 Bn | 6.34 Bn | - | 58.19 Mn |
| 9 | Ares Capital | 13.90 Bn | 11.34 Bn | - | - |
| 10 | Mfa Financial | 809.71 Mn | -71.50 Mn | - | 41.52 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 41.52 Mn |
| Mar 31, 2026 | 44.53 Mn |
| Dec 31, 2025 | 34.67 Mn |
| Sep 30, 2025 | 39.47 Mn |
| Jun 30, 2025 | 39.31 Mn |
| Mar 31, 2025 | 41.60 Mn |
| Dec 31, 2024 | 39.86 Mn |
| Sep 30, 2024 | 43.15 Mn |
| Jun 30, 2024 | 42.10 Mn |
| Mar 31, 2024 | 45.31 Mn |
| Dec 31, 2023 | 40.75 Mn |
| Sep 30, 2023 | 43.92 Mn |
| Jun 30, 2023 | 42.19 Mn |
| Mar 31, 2023 | 41.70 Mn |
| Dec 31, 2022 | 34.22 Mn |
| Sep 30, 2022 | 42.53 Mn |
| Jun 30, 2022 | 46.10 Mn |
| Mar 31, 2022 | 41.95 Mn |
| Dec 31, 2021 | 41.43 Mn |
| Sep 30, 2021 | 33.46 Mn |
Mfa Financial 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=MFA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MFA", "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=MFA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();