German American Bancorp (GABC) Return on Sales [ROS] (2009 - 2026)
German American Bancorp (GABC) reported Return on Sales [ROS] of 615.79% for Q2 2026, down 26.00 percentage points from 641.78% a year earlier but up 5.44 percentage points from the prior quarter.
German American Bancorp (GABC) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, German American Bancorp's Return on Sales [ROS] came in at 612.24%, up 68.08 percentage points year-over-year; for FY2025, it was 578.40%, up 77.12 percentage points from FY2024.
- Return on Sales [ROS] has increased for five consecutive years, with a five-year change of +324.92 percentage points (FY2020 to FY2025).
- By year, Return on Sales [ROS] came in at 501.28% in FY2024 (+37.04 pp), 464.24% in FY2023 (+130.56 pp), 333.68% in FY2022 (+74.28 pp) and 259.40% in FY2021 (+5.92 pp).
- Five-year quarterly Return on Sales [ROS] spans a low of 90.14% in Q1 2022 and a high of 641.78% in Q2 2025.
- Year over year, Return on Sales [ROS] gained in six of the last eight quarters, with an average year-over-year change of +88.00 percentage points.
- The high point for year-over-year Return on Sales [ROS] in five years was Q1 2024 (a gain of 244.86 percentage points); the low point was Q1 2022 (a drop of 157.56 percentage points).
- Per Business Quant data, the three quarters before Q2 2026 came in at 610.34% (Q1 2026), 637.53% (Q4 2025) and 587.75% (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 909.02 Bn | 886.77 Bn | - | 91.99% |
| 2 | Banco Santander Chile | 406.67 Bn | -7,110.43 Bn | - | - |
| 3 | Bank Of America | 350.91 Bn | -2,025.20 Bn | - | 89.38% |
| 4 | Hsbc Holdings | 308.71 Bn | -2,966.46 Bn | - | 48.15% |
| 5 | Morgan Stanley | 293.66 Bn | -249.15 Bn | - | 95.47% |
| 6 | Royal Bank Of Canada | 283.56 Bn | -546.44 Bn | - | 138.04% |
| 7 | Goldman Sachs | 262.71 Bn | -3,480.74 Bn | - | 139.33% |
| 8 | Wells Fargo & Company | 257.44 Bn | 92.87 Bn | - | 84.54% |
| 9 | Mitsubishi Ufj Financial | 256.82 Bn | -75.42 Bn | 10.89 Bn | 51.45% |
| 10 | German American Bancorp | 1.88 Bn | 1.47 Bn | - | 74.28% |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 74.28% |
| Jun 30, 2026 | 75.08% |
| Mar 31, 2026 | 71.37% |
| Dec 31, 2025 | 77.59% |
| Sep 30, 2025 | 80.85% |
| Jun 30, 2025 | 80.60% |
| Mar 31, 2025 | 52.79% |
| Dec 31, 2024 | 83.21% |
| Sep 30, 2024 | 82.86% |
| Jun 30, 2024 | 80.44% |
| Mar 31, 2024 | 76.36% |
| Dec 31, 2023 | 76.59% |
| Sep 30, 2023 | 70.76% |
| Jun 30, 2023 | 66.72% |
| Mar 31, 2023 | 57.43% |
| Dec 31, 2022 | 58.16% |
| Sep 30, 2022 | 54.04% |
| Jun 30, 2022 | 48.54% |
| Mar 31, 2022 | 19.18% |
| Dec 31, 2021 | 44.32% |
German American Bancorp Return on Sales [ROS] 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=return-on-sales-%5Bros%5D&ticker=GABC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "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=return-on-sales-%5Bros%5D&ticker=GABC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();