Hope Bancorp (HOPE) Operating Expenses (2010 - 2026)
Hope Bancorp's Operating Expenses was $98.46 million in Q2 2026, down 10.1% from $109.47 million a year earlier but up 4.2% from the prior quarter.
Hope Bancorp (HOPE) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Hope Bancorp's Operating Expenses was $389.21 million through Jun 30, 2026, up 10.5% year-over-year; for FY2025, it came in at $389.62 million, up 20.0% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 6.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $324.68 million in FY2024 (-10.3%), $361.96 million in FY2023 (+11.7%), $323.92 million in FY2022 (+10.4%) and $293.29 million in FY2021 (+3.4%).
- Quarterly Operating Expenses has moved between $74.24 million (Q4 2021) and $109.47 million (Q2 2025) over five years.
- Compared with a year earlier, Operating Expenses was higher in four of the last eight quarters, with growth averaging 7.0%.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2025 (growth of 35.2%); the worst was Q4 2024 (a decline of 21.8%).
- Per Business Quant data, HOPE's Operating Expenses in the three quarters before Q2 2026 was $94.46 million (Q1 2026), $99.43 million (Q4 2025) and $96.86 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 890.60 Bn | 920.07 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 421.74 Bn | 541.68 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 385.85 Bn | -1,990.22 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 345.94 Bn | 345.99 Bn | - | - |
| 5 | Morgan Stanley | 303.15 Bn | -205.95 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 279.82 Bn | 130.57 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 274.62 Bn | -1,313.87 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 267.07 Bn | -3,290.04 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 243.79 Bn | 245.93 Bn | - | 13.66 Bn |
| 10 | Hope Bancorp | 1.72 Bn | -753.18 Mn | - | 98.46 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 98.46 Mn |
| Mar 31, 2026 | 94.46 Mn |
| Dec 31, 2025 | 99.43 Mn |
| Sep 30, 2025 | 96.86 Mn |
| Jun 30, 2025 | 109.47 Mn |
| Mar 31, 2025 | 83.86 Mn |
| Dec 31, 2024 | 77.59 Mn |
| Sep 30, 2024 | 81.27 Mn |
| Jun 30, 2024 | 80.99 Mn |
| Mar 31, 2024 | 84.84 Mn |
| Dec 31, 2023 | 99.19 Mn |
| Sep 30, 2023 | 86.81 Mn |
| Jun 30, 2023 | 87.22 Mn |
| Mar 31, 2023 | 88.73 Mn |
| Dec 31, 2022 | 84.52 Mn |
| Sep 30, 2022 | 83.91 Mn |
| Jun 30, 2022 | 80.37 Mn |
| Mar 31, 2022 | 75.37 Mn |
| Dec 31, 2021 | 74.24 Mn |
| Sep 30, 2021 | 75.50 Mn |
Hope Bancorp 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=HOPE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HOPE", "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=HOPE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();