Upbound (UPBD) Operating Expenses (2009 - 2026)
Upbound (UPBD) posted Operating Expenses of $540.58 million for Q2 2026, up 3.7% from $521.09 million a year earlier and up 6.2% from the prior quarter.
Upbound (UPBD) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Upbound was $2.09 billion, up 11.2% year-over-year; for FY2025, it was $2.05 billion, up 14.5% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 7.4% (FY2020 to FY2025).
- In prior years, Upbound's Operating Expenses was $1.79 billion in FY2024 (-3.8%), $1.86 billion in FY2023 (-3.7%), $1.93 billion in FY2022 (-1.2%) and $1.95 billion in FY2021 (+36.2%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q1 2023.
- On a year-over-year basis, Operating Expenses has increased in each of the last six quarters, with growth averaging 7.7% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2021, with growth of 45.5%; the weakest was Q4 2022, with a decline of 14.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $509.02 million (Q1 2026), $529.43 million (Q4 2025) and $510.32 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Orix | 43.85 Bn | 44.35 Bn | - | 4.66 Bn |
| 2 | Rocket Companies | 43.67 Bn | 29.35 Bn | - | 2.50 Bn |
| 3 | Royalty Pharma | 33.56 Bn | 33.48 Bn | - | 541.02 Mn |
| 4 | Federal National Mortgage Association Fannie Mae | 25.52 Bn | 25.52 Bn | - | 2.07 Bn |
| 5 | Synchrony Financial | 23.24 Bn | -44.73 Bn | - | 1.33 Bn |
| 6 | Affirm Holdings | 22.66 Bn | 16.35 Bn | - | 1.02 Bn |
| 7 | Royal Gold | 20.35 Bn | 19.57 Bn | 390.45 Mn | 173.18 Mn |
| 8 | Annaly Capital Management | 15.27 Bn | 6.37 Bn | - | 58.19 Mn |
| 9 | Ares Capital | 13.74 Bn | 11.17 Bn | - | - |
| 10 | Upbound | 920.55 Mn | 489.28 Mn | 594.84 Mn | 540.58 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 540.58 Mn |
| Mar 31, 2026 | 509.02 Mn |
| Dec 31, 2025 | 529.43 Mn |
| Sep 30, 2025 | 510.32 Mn |
| Jun 30, 2025 | 521.09 Mn |
| Mar 31, 2025 | 487.51 Mn |
| Dec 31, 2024 | 429.08 Mn |
| Sep 30, 2024 | 441.03 Mn |
| Jun 30, 2024 | 451.30 Mn |
| Mar 31, 2024 | 467.31 Mn |
| Dec 31, 2023 | 456.71 Mn |
| Sep 30, 2023 | 439.11 Mn |
| Jun 30, 2023 | 422.20 Mn |
| Mar 31, 2023 | 541.38 Mn |
| Dec 31, 2022 | 453.02 Mn |
| Sep 30, 2022 | 468.46 Mn |
| Jun 30, 2022 | 474.46 Mn |
| Mar 31, 2022 | 535.05 Mn |
| Dec 31, 2021 | 531.43 Mn |
| Sep 30, 2021 | 501.61 Mn |
Upbound 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=UPBD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "UPBD", "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=UPBD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();