Oak Valley Bancorp (OVLY) Operating Expenses (2009 - 2026)
Oak Valley Bancorp (OVLY) recorded Operating Expenses of $13.42 million in Q3 2026, up 5.7% from $12.7 million a year earlier but down 5.2% from the prior quarter.
Oak Valley Bancorp (OVLY) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Oak Valley Bancorp's Operating Expenses came in at $53.35 million as of Sep 30, 2026, up 8.8% year-over-year; for FY2025, it was $50.27 million, up 9.3% from FY2024.
- Annual Operating Expenses has increased for 15 straight years, with a five-year compound annual growth rate of 11.0% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $46.02 million in FY2024 (+11.8%), $41.16 million in FY2023 (+10.3%), $37.31 million in FY2022 (+12.3%) and $33.22 million in FY2021 (+11.2%).
- Quarterly Operating Expenses has ranged from $8.88 million in Q4 2021 to $14.16 million in Q2 2026 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for 25 consecutive quarters, with growth averaging 8.6% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 5.7% (Q3 2026) and 18.2% (Q1 2024) over the last five years.
- Per Business Quant, the preceding three quarters came in at $14.16 million (Q2 2026), $13.51 million (Q1 2026) and $12.26 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 | Oak Valley Bancorp | 288.38 Mn | -533.48 Mn | - | 13.42 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 13.42 Mn |
| Jun 30, 2026 | 14.16 Mn |
| Mar 31, 2026 | 13.51 Mn |
| Dec 31, 2025 | 12.78 Mn |
| Sep 30, 2025 | 12.70 Mn |
| Jun 30, 2025 | 12.44 Mn |
| Mar 31, 2025 | 12.35 Mn |
| Dec 31, 2024 | 11.55 Mn |
| Sep 30, 2024 | 11.32 Mn |
| Jun 30, 2024 | 11.62 Mn |
| Mar 31, 2024 | 11.53 Mn |
| Dec 31, 2023 | 10.76 Mn |
| Sep 30, 2023 | 10.58 Mn |
| Jun 30, 2023 | 10.06 Mn |
| Mar 31, 2023 | 9.76 Mn |
| Dec 31, 2022 | 9.61 Mn |
| Sep 30, 2022 | 9.37 Mn |
| Jun 30, 2022 | 9.21 Mn |
| Mar 31, 2022 | 9.12 Mn |
| Dec 31, 2021 | 8.88 Mn |
Oak Valley 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=OVLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "OVLY", "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=OVLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();