Cathay General Bancorp (CATY) Operating Expenses (2009 - 2026)
Cathay General Bancorp's Operating Expenses was $103.38 million in Q3 2026, up 17.3% from $88.12 million a year earlier and up 12.0% from the prior quarter.
Cathay General Bancorp (CATY) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Cathay General Bancorp's Operating Expenses was $374.53 million through Sep 30, 2026, up 7.6% year-over-year; for FY2025, it came in at $355.06 million, down 5.2% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 4.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $374.68 million in FY2024 (-1.5%), $380.48 million in FY2023 (+25.4%), $303.43 million in FY2022 (+5.9%) and $286.52 million in FY2021 (+1.1%).
- The Q3 2026 figure marks the highest quarterly Operating Expenses since Q4 2023.
- Compared with a year earlier, Operating Expenses has increased for four straight quarters, with an average decline of 2.5% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2023 (growth of 36.0%); the worst was Q4 2024 (a decline of 22.9%).
- Per Business Quant data, CATY's Operating Expenses in the three quarters before Q3 2026 was $92.32 million (Q2 2026), $86.68 million (Q1 2026) and $92.16 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | 8.82 Bn |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 11.31 Bn |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 13.74 Bn |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | 17.50 Bn |
| 10 | Cathay General Bancorp | 4.32 Bn | 4.22 Bn | - | 103.38 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 103.38 Mn |
| Jun 30, 2026 | 92.32 Mn |
| Mar 31, 2026 | 86.68 Mn |
| Dec 31, 2025 | 92.16 Mn |
| Sep 30, 2025 | 88.12 Mn |
| Jun 30, 2025 | 89.13 Mn |
| Mar 31, 2025 | 85.66 Mn |
| Dec 31, 2024 | 85.22 Mn |
| Sep 30, 2024 | 96.87 Mn |
| Jun 30, 2024 | 99.35 Mn |
| Mar 31, 2024 | 93.24 Mn |
| Dec 31, 2023 | 110.50 Mn |
| Sep 30, 2023 | 93.97 Mn |
| Jun 30, 2023 | 92.82 Mn |
| Mar 31, 2023 | 83.19 Mn |
| Dec 31, 2022 | 81.22 Mn |
| Sep 30, 2022 | 75.39 Mn |
| Jun 30, 2022 | 74.12 Mn |
| Mar 31, 2022 | 72.70 Mn |
| Dec 31, 2021 | 73.20 Mn |
Cathay General 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=CATY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CATY", "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=CATY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();