Plumas Bancorp (PLBC) Operating Expenses (2010 - 2026)
Plumas Bancorp (PLBC) reported Operating Expenses of $14.5 million for Q2 2026, up 31.7% from $11.01 million a year earlier but down 5.1% from the prior quarter.
Plumas Bancorp (PLBC) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Plumas Bancorp's Operating Expenses came in at $59.17 million, up 34.6% year-over-year; for FY2025, it came in at $51.85 million, up 22.7% from FY2024.
- Operating Expenses has increased for 12 consecutive years, with a five-year compound annual growth rate of 16.9% (FY2020 to FY2025).
- By year, Operating Expenses came in at $42.27 million in FY2024 (+12.6%), $37.53 million in FY2023 (+15.2%), $32.59 million in FY2022 (+25.2%) and $26.04 million in FY2021 (+9.7%).
- Five-year quarterly Operating Expenses spans a low of $6.6 million in Q3 2021 and a high of $15.29 million in Q1 2026.
- Year over year, Operating Expenses has now increased in each of the last 20 quarters, with growth averaging 22.3% over the last eight quarters.
- Over the past five years, the year-over-year growth in Operating Expenses ranged from 5.9% (Q2 2025) to 50.7% (Q2 2022).
- Per Business Quant data, the three quarters before Q2 2026 came in at $15.29 million (Q1 2026), $14.24 million (Q4 2025) and $15.13 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 879.54 Bn | 909.01 Bn | - | 27.32 Bn |
| 2 | Banco Santander Chile | 418.48 Bn | 538.42 Bn | - | -3,218.32 Bn |
| 3 | Bank Of America | 381.92 Bn | -1,994.15 Bn | - | 18.63 Bn |
| 4 | Hsbc Holdings | 341.10 Bn | 341.15 Bn | - | - |
| 5 | Morgan Stanley | 295.71 Bn | -213.38 Bn | - | 13.90 Bn |
| 6 | Royal Bank Of Canada | 275.38 Bn | 126.13 Bn | - | 7.02 Bn |
| 7 | Mitsubishi Ufj Financial | 273.79 Bn | -1,314.70 Bn | 10.89 Bn | 17.50 Bn |
| 8 | Goldman Sachs | 262.78 Bn | -3,294.34 Bn | - | 11.67 Bn |
| 9 | Wells Fargo & Company | 242.61 Bn | 244.75 Bn | - | 13.66 Bn |
| 10 | Plumas Bancorp | 426.59 Mn | 60.27 Mn | - | 14.50 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.50 Mn |
| Mar 31, 2026 | 15.29 Mn |
| Dec 31, 2025 | 14.24 Mn |
| Sep 30, 2025 | 15.13 Mn |
| Jun 30, 2025 | 11.01 Mn |
| Mar 31, 2025 | 11.47 Mn |
| Dec 31, 2024 | 10.66 Mn |
| Sep 30, 2024 | 10.82 Mn |
| Jun 30, 2024 | 10.40 Mn |
| Mar 31, 2024 | 10.40 Mn |
| Dec 31, 2023 | 9.77 Mn |
| Sep 30, 2023 | 9.44 Mn |
| Jun 30, 2023 | 9.10 Mn |
| Mar 31, 2023 | 9.22 Mn |
| Dec 31, 2022 | 8.69 Mn |
| Sep 30, 2022 | 8.20 Mn |
| Jun 30, 2022 | 8.03 Mn |
| Mar 31, 2022 | 7.67 Mn |
| Dec 31, 2021 | 7.81 Mn |
| Sep 30, 2021 | 6.60 Mn |
Plumas 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=PLBC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PLBC", "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=PLBC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();