Dream Finders Homes (DFH) Operating Expenses (2020 - 2026)
Dream Finders Homes (DFH) posted Operating Expenses of $128.44 million for Q2 2026, down 4.6% from $134.7 million a year earlier but up 15.8% from the prior quarter.
Dream Finders Homes (DFH) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Dream Finders Homes was $473.16 million, up 0.8% year-over-year; for FY2025, it came in at $485.21 million, up 22.8% from FY2024.
- Annual Operating Expenses has increased for six consecutive years, with a five-year compound annual growth rate of 40.0% (FY2020 to FY2025).
- In prior years, Dream Finders Homes' Operating Expenses was $395.1 million in FY2024 (+30.5%), $302.79 million in FY2023 (+13.8%), $266.07 million in FY2022 (+72.3%) and $154.41 million in FY2021 (+70.9%).
- Quarterly Operating Expenses has run from a low of $33.91 million in Q3 2021 to a high of $134.7 million in Q2 2025 over five years.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 18.2%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q2 2022, with growth of 119.0%; the weakest was Q1 2026, with a decline of 5.0%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $110.9 million (Q1 2026), $124.31 million (Q4 2025) and $109.51 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Horton D R | 39.14 Bn | 30.03 Bn | 2.15 Bn | 991.20 Mn |
| 2 | Pultegroup | 22.34 Bn | 15.63 Bn | 1.06 Bn | 382.97 Mn |
| 3 | Lennar | 17.27 Bn | 6.70 Bn | 807.31 Mn | 7.54 Bn |
| 4 | Nvr | 16.72 Bn | 10.01 Bn | 485.14 Mn | 150.72 Mn |
| 5 | Toll Brothers | 12.58 Bn | 7.96 Bn | 625.22 Mn | 266.07 Mn |
| 6 | Taylor Morrison Home | 6.77 Bn | 4.76 Bn | 290.64 Mn | 58.97 Mn |
| 7 | Champion Homes | 4.80 Bn | 2.28 Bn | - | - |
| 8 | Cavco Industries | 4.31 Bn | 3.07 Bn | - | - |
| 9 | Meritage Homes | 4.24 Bn | 1.16 Bn | 513.60 Mn | 52.38 Mn |
| 10 | Dream Finders Homes | 993.34 Mn | -101.80 Mn | 154.40 Mn | 128.44 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 128.44 Mn |
| Mar 31, 2026 | 110.90 Mn |
| Dec 31, 2025 | 124.31 Mn |
| Sep 30, 2025 | 109.51 Mn |
| Jun 30, 2025 | 134.70 Mn |
| Mar 31, 2025 | 116.69 Mn |
| Dec 31, 2024 | 116.44 Mn |
| Sep 30, 2024 | 101.70 Mn |
| Jun 30, 2024 | 96.85 Mn |
| Mar 31, 2024 | 80.11 Mn |
| Dec 31, 2023 | 92.24 Mn |
| Sep 30, 2023 | 78.51 Mn |
| Jun 30, 2023 | 73.71 Mn |
| Mar 31, 2023 | 60.76 Mn |
| Dec 31, 2022 | 69.50 Mn |
| Sep 30, 2022 | 68.84 Mn |
| Jun 30, 2022 | 66.02 Mn |
| Mar 31, 2022 | 61.71 Mn |
| Dec 31, 2021 | 61.05 Mn |
| Sep 30, 2021 | 33.91 Mn |
Dream Finders Homes 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=DFH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DFH", "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=DFH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();