Landmark Bancorp (LARK) Return on Sales [ROS] (2009 - 2026)
Landmark Bancorp (LARK) posted Return on Sales [ROS] of 61.45% for Q1 2026, down 11.01 percentage points from 72.46% a year earlier and down 2.64 percentage points from the prior quarter.
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Analysis
Landmark Bancorp (LARK) Return on Sales [ROS] (2009 - 2026) Analysis & Trends
For the trailing twelve months through Mar 31, 2026, Return on Sales [ROS] at Landmark Bancorp was 65.79%, down 4.13 percentage points year-over-year; for FY2025, it was 68.50%, down 1.40 percentage points from FY2024.
- Annual Return on Sales [ROS] shows a five-year change of +26.13 percentage points (FY2020 to FY2025).
- In prior years, Landmark Bancorp's Return on Sales [ROS] was 69.89% in FY2024 (+6.94 pp), 62.95% in FY2023 (+33.18 pp), 29.78% in FY2022 (-10.39 pp) and 40.16% in FY2021 (-2.21 pp).
- The Q1 2026 figure stands as the lowest quarterly Return on Sales [ROS] since Q4 2024.
- On a year-over-year basis, Return on Sales [ROS] increased in three of the last eight quarters, with an average year-over-year change of -1.08 percentage points.
- The strongest year-over-year quarter for Return on Sales [ROS] in the past five years was Q4 2023, with a gain of 48.36 percentage points; the weakest was Q4 2024, with a drop of 12.72 percentage points.
- According to Business Quant data, Return on Sales [ROS] for the three prior quarters was 64.08% (Q4 2025), 69.96% (Q3 2025) and 67.96% (Q2 2025).
Peer Set
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 | Landmark Bancorp | 195.20 Mn | 84.43 Mn | - | 62.33% |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 62.33% |
| Jun 30, 2026 | 61.98% |
| Mar 31, 2026 | 61.45% |
| Dec 31, 2025 | 64.08% |
| Sep 30, 2025 | 69.96% |
| Jun 30, 2025 | 67.96% |
| Mar 31, 2025 | 72.46% |
| Dec 31, 2024 | 56.75% |
| Sep 30, 2024 | 77.04% |
| Jun 30, 2024 | 73.53% |
| Mar 31, 2024 | 72.76% |
| Dec 31, 2023 | 69.47% |
| Sep 30, 2023 | 68.06% |
| Jun 30, 2023 | 61.77% |
| Mar 31, 2023 | 53.18% |
| Dec 31, 2022 | 21.11% |
| Sep 30, 2022 | 32.04% |
| Jun 30, 2022 | 33.11% |
| Mar 31, 2022 | 34.33% |
| Dec 31, 2021 | 32.97% |
API Access
Landmark 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=LARK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "LARK", "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=LARK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();