Mid Penn Bancorp (MPB) EBITDA (2010 - 2026)
Mid Penn Bancorp (MPB) posted EBITDA of $62.35 million for Q2 2026, up 64.0% from $38.01 million a year earlier and up 45.8% from the prior quarter.
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Analysis
Mid Penn Bancorp (MPB) EBITDA (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EBITDA at Mid Penn Bancorp was $224.49 million, up 20.8% year-over-year; for FY2025, it came in at $204.99 million, up 4.3% from FY2024.
- Annual EBITDA has increased for four consecutive years, with a five-year compound annual growth rate of 29.8% (FY2020 to FY2025).
- In prior years, Mid Penn Bancorp's EBITDA was $196.63 million in FY2024 (+39.7%), $140.74 million in FY2023 (+53.9%), $91.43 million in FY2022 (+65.3%) and $55.3 million in FY2021 (-0.7%).
- The Q2 2026 figure stands as the highest quarterly EBITDA in data going back to Q3 2010.
- On a year-over-year basis, EBITDA increased in five of the last eight quarters, with growth averaging 13.5%.
- The strongest year-over-year quarter for EBITDA in the past five years was Q4 2022, with growth of 471.2%; the weakest was Q4 2021, with a decline of 68.6%.
- According to Business Quant data, EBITDA for the three prior quarters was $42.77 million (Q1 2026), $59.75 million (Q4 2025) and $59.63 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 895.36 Bn | 924.83 Bn | - | 54.95 Bn |
| 2 | Banco Santander Chile | 425.01 Bn | 544.95 Bn | - | -1,174.27 Bn |
| 3 | Bank Of America | 389.22 Bn | -1,986.85 Bn | - | 30.01 Bn |
| 4 | Hsbc Holdings | 347.56 Bn | 347.61 Bn | - | - |
| 5 | Morgan Stanley | 304.44 Bn | -204.66 Bn | - | 21.67 Bn |
| 6 | Royal Bank Of Canada | 281.54 Bn | 132.29 Bn | - | 18.88 Bn |
| 7 | Mitsubishi Ufj Financial | 277.23 Bn | -1,311.26 Bn | 10.89 Bn | - |
| 8 | Goldman Sachs | 267.12 Bn | -3,289.99 Bn | - | 27.17 Bn |
| 9 | Wells Fargo & Company | 244.76 Bn | 246.90 Bn | - | 20.89 Bn |
| 10 | Mid Penn Bancorp | 912.56 Mn | 895.87 Mn | - | 62.35 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 62.35 Mn |
| Mar 31, 2026 | 42.77 Mn |
| Dec 31, 2025 | 59.75 Mn |
| Sep 30, 2025 | 59.63 Mn |
| Jun 30, 2025 | 38.01 Mn |
| Mar 31, 2025 | 47.60 Mn |
| Dec 31, 2024 | 49.92 Mn |
| Sep 30, 2024 | 50.24 Mn |
| Jun 30, 2024 | 48.41 Mn |
| Mar 31, 2024 | 48.07 Mn |
| Dec 31, 2023 | 45.26 Mn |
| Sep 30, 2023 | 39.18 Mn |
| Jun 30, 2023 | 26.77 Mn |
| Mar 31, 2023 | 29.54 Mn |
| Dec 31, 2022 | 29.20 Mn |
| Sep 30, 2022 | 24.28 Mn |
| Jun 30, 2022 | 19.36 Mn |
| Mar 31, 2022 | 18.58 Mn |
| Dec 31, 2021 | 5.11 Mn |
| Sep 30, 2021 | 16.12 Mn |
API Access
Mid Penn Bancorp EBITDA 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=ebitda&ticker=MPB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=MPB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();