Magyar Bancorp (MGYR) Return on Sales [ROS] (2010 - 2026)
Magyar Bancorp (MGYR) recorded Return on Sales [ROS] of 107.54% in fiscal Q3 2024 (quarter ended Jun 30, 2024), up 33.07 percentage points from 74.46% a year earlier and up 9.19 percentage points from the prior quarter.
Magyar Bancorp (MGYR) Return on Sales [ROS] (2010 - 2026) Analysis & Trends
On a TTM basis, Magyar Bancorp's Return on Sales [ROS] came in at 92.96% as of Jun 30, 2024, up 31.22 percentage points year-over-year; for FY2023 (ended Sep 30, 2023), it was 69.29%, up 23.37 percentage points from FY2022.
- Annual Return on Sales [ROS] has increased for three straight fiscal years, with a five-year change of +31.94 percentage points (FY2018 to FY2023).
- Across earlier fiscal years, Return on Sales [ROS] came in at 45.92% in FY2022 (+5.68 pp), 40.23% in FY2021 (+2.95 pp), 37.28% in FY2020 (-11.41 pp) and 48.70% in FY2019 (+11.35 pp).
- The fiscal Q3 2024 figure is the highest quarterly Return on Sales [ROS] in data going back to fiscal Q3 2020.
- On a year-over-year basis, Return on Sales [ROS] has increased for 13 consecutive quarters, with an average year-over-year change of +25.48 percentage points over the last eight quarters.
- The year-over-year gain in Return on Sales [ROS] has ranged between 1.99 percentage points (fiscal Q2 2022) and 34.81 percentage points (fiscal Q2 2024) over the last five years.
- Per Business Quant, the preceding three fiscal quarters came in at 98.34% (Q2 2024), 84.87% (Q1 2024) and 82.51% (Q4 2023).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | ROS (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 881.30 Bn | 881.30 Bn | - | 91.77% |
| 2 | Bank Of America | 354.90 Bn | -2,021.17 Bn | - | 93.16% |
| 3 | Hsbc Holdings | 311.39 Bn | -1,517.77 Bn | - | 46.36% |
| 4 | Morgan Stanley | 282.15 Bn | -226.95 Bn | - | 95.89% |
| 5 | Royal Bank Of Canada | 281.68 Bn | -548.32 Bn | - | 138.04% |
| 6 | Goldman Sachs | 255.22 Bn | -3,301.89 Bn | - | 131.07% |
| 7 | Mitsubishi Ufj Financial | 249.82 Bn | -82.42 Bn | 10.89 Bn | 51.45% |
| 8 | Wells Fargo & Company | 249.49 Bn | 251.62 Bn | - | 84.05% |
| 9 | Toronto Dominion Bank | 210.53 Bn | -465.35 Bn | - | 6.25% |
| 10 | Magyar Bancorp | 128.50 Mn | 28.19 Mn | - | 102.06% |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 102.06% |
| Mar 31, 2026 | 100.97% |
| Dec 31, 2025 | 105.62% |
| Sep 30, 2025 | 106.51% |
| Jun 30, 2025 | 108.99% |
| Mar 31, 2025 | 105.03% |
| Dec 31, 2024 | 104.39% |
| Sep 30, 2024 | 131.08% |
| Jun 30, 2024 | 107.54% |
| Mar 31, 2024 | 98.34% |
| Dec 31, 2023 | 84.87% |
| Sep 30, 2023 | 82.51% |
| Jun 30, 2023 | 74.46% |
| Mar 31, 2023 | 63.53% |
| Dec 31, 2022 | 56.09% |
| Sep 30, 2022 | 53.44% |
| Jun 30, 2022 | 46.01% |
| Mar 31, 2022 | 41.66% |
| Dec 31, 2021 | 41.43% |
| Sep 30, 2021 | 40.36% |
Magyar 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=MGYR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "return-on-sales-[ros]", "ticker": "MGYR", "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=MGYR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();