German American Bancorp (GABC) EBITDA (2012 - 2026)
German American Bancorp (GABC) reported EBITDA of $79.81 million for Q2 2026, up 3.3% from $77.25 million a year earlier and up 8.7% from the prior quarter.
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Analysis
German American Bancorp (GABC) EBITDA (2012 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, German American Bancorp's EBITDA came in at $314.03 million, up 33.9% year-over-year; for FY2025, it was $284.74 million, up 33.2% from FY2024.
- EBITDA has increased for five consecutive years, with a five-year compound annual growth rate of 22.4% (FY2020 to FY2025).
- By year, EBITDA came in at $213.83 million in FY2024 (+19.2%), $179.43 million in FY2023 (+40.6%), $127.63 million in FY2022 (+5.4%) and $121.1 million in FY2021 (+16.9%).
- Five-year quarterly EBITDA spans a low of $14.76 million in Q1 2022 and a high of $81.29 million in Q3 2025.
- Year over year, EBITDA has now increased in each of the last five quarters, with growth averaging 27.5% over the last eight quarters.
- The high point for year-over-year EBITDA in five years was Q1 2023 (growth of 165.4%); the low point was Q1 2022 (a decline of 49.3%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $73.45 million (Q1 2026), $79.48 million (Q4 2025) and $81.29 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 879.54 Bn | 909.01 Bn | - | 54.95 Bn |
| 2 | Banco Santander Chile | 418.48 Bn | 538.42 Bn | - | -1,174.27 Bn |
| 3 | Bank Of America | 381.92 Bn | -1,994.15 Bn | - | 30.01 Bn |
| 4 | Hsbc Holdings | 341.10 Bn | 341.15 Bn | - | - |
| 5 | Morgan Stanley | 295.71 Bn | -213.38 Bn | - | 21.67 Bn |
| 6 | Royal Bank Of Canada | 275.38 Bn | 126.13 Bn | - | 18.88 Bn |
| 7 | Mitsubishi Ufj Financial | 273.79 Bn | -1,314.70 Bn | 10.89 Bn | - |
| 8 | Goldman Sachs | 262.78 Bn | -3,294.34 Bn | - | 27.17 Bn |
| 9 | Wells Fargo & Company | 242.61 Bn | 244.75 Bn | - | 20.89 Bn |
| 10 | German American Bancorp | 1.82 Bn | 1.82 Bn | - | 79.81 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 79.81 Mn |
| Mar 31, 2026 | 73.45 Mn |
| Dec 31, 2025 | 79.48 Mn |
| Sep 30, 2025 | 81.29 Mn |
| Jun 30, 2025 | 77.25 Mn |
| Mar 31, 2025 | 46.72 Mn |
| Dec 31, 2024 | 56.52 Mn |
| Sep 30, 2024 | 54.00 Mn |
| Jun 30, 2024 | 54.53 Mn |
| Mar 31, 2024 | 48.78 Mn |
| Dec 31, 2023 | 49.22 Mn |
| Sep 30, 2023 | 46.49 Mn |
| Jun 30, 2023 | 44.55 Mn |
| Mar 31, 2023 | 39.17 Mn |
| Dec 31, 2022 | 40.79 Mn |
| Sep 30, 2022 | 38.05 Mn |
| Jun 30, 2022 | 34.04 Mn |
| Mar 31, 2022 | 14.76 Mn |
| Dec 31, 2021 | 26.73 Mn |
| Sep 30, 2021 | 30.83 Mn |
API Access
German American 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=GABC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "GABC", "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=GABC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();