Mid Penn Bancorp (MPB) Operating Expenses (2009 - 2026)
Mid Penn Bancorp (MPB) recorded Operating Expenses of $47.77 million in Q2 2026, down 0.1% from $47.8 million a year earlier and down 8.1% from the prior quarter.
Powered by 
Analysis
Mid Penn Bancorp (MPB) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Mid Penn Bancorp's Operating Expenses came in at $173.56 million as of Jun 30, 2026, up 24.6% year-over-year; for FY2025, it was $152.27 million, up 29.5% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 16.6% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $117.62 million in FY2024 (-0.8%), $118.59 million in FY2023 (+18.8%), $99.84 million in FY2022 (+9.6%) and $91.11 million in FY2021 (+29.1%).
- Quarterly Operating Expenses has ranged from $20.02 million in Q3 2021 to $51.96 million in Q1 2026 over the past five years.
- On a year-over-year basis, Operating Expenses rose in seven of the last eight quarters, with growth averaging 25.1%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 69.6% in Q1 2026, against a decline of 25.3% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $51.96 million (Q1 2026), $35.85 million (Q4 2025) and $37.98 million (Q3 2025).
Peer Set
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 | Mid Penn Bancorp | 881.41 Mn | 364.13 Mn | - | 48.59 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 48.59 Mn |
| Jun 30, 2026 | 47.77 Mn |
| Mar 31, 2026 | 51.96 Mn |
| Dec 31, 2025 | 35.85 Mn |
| Sep 30, 2025 | 37.98 Mn |
| Jun 30, 2025 | 47.80 Mn |
| Mar 31, 2025 | 30.64 Mn |
| Dec 31, 2024 | 30.91 Mn |
| Sep 30, 2024 | 29.96 Mn |
| Jun 30, 2024 | 28.22 Mn |
| Mar 31, 2024 | 28.52 Mn |
| Dec 31, 2023 | 28.39 Mn |
| Sep 30, 2023 | 29.23 Mn |
| Jun 30, 2023 | 35.13 Mn |
| Mar 31, 2023 | 25.84 Mn |
| Dec 31, 2022 | 25.47 Mn |
| Sep 30, 2022 | 24.72 Mn |
| Jun 30, 2022 | 23.92 Mn |
| Mar 31, 2022 | 25.75 Mn |
| Dec 31, 2021 | 34.07 Mn |
API Access
Mid Penn 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=MPB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MPB", "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=MPB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();