Magyar Bancorp (MGYR) Weighted Average Shares Outstanding (2009 - 2026)
Magyar Bancorp (MGYR) recorded Weighted Average Shares Outstanding of 6.22 million in fiscal Q4 2026 (quarter ended Sep 30, 2026), down 0.1% from 6.22 million a year earlier and unchanged from the prior quarter.
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Analysis
Magyar Bancorp (MGYR) Weighted Average Shares Outstanding (2009 - 2026) Analysis & Trends
Starting with fiscal Q3 2011, Magyar Bancorp's Weighted Average Shares Outstanding history includes 62 quarters.
- Annual Weighted Average Shares Outstanding has declined for four straight fiscal years, though with a five-year compound annual growth rate of 0.6% (FY2021 to FY2026).
- Across earlier fiscal years, Weighted Average Shares Outstanding came in at 6.22 million in FY2025 (-1.9%), 6.34 million in FY2024 (-1.3%), 6.42 million in FY2023 (-5.3%) and 6.78 million in FY2022 (+12.3%).
- Quarterly Weighted Average Shares Outstanding has ranged from 6.21 million in fiscal Q1 2026 to 6.8 million in fiscal Q3 2022 over the past five years.
- Peak year-over-year performance for Weighted Average Shares Outstanding in the last five years was growth of 17.0% in fiscal Q3 2022, against a decline of 5.7% in fiscal Q3 2023 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at 6.22 million (Q3 2026), 6.22 million (Q2 2026) and 6.21 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Jpmorgan Chase | 920.14 Bn | 897.90 Bn | - |
| 2 | Banco Santander Chile | 407.42 Bn | -7,109.68 Bn | - |
| 3 | Bank Of America | 353.20 Bn | -2,022.91 Bn | - |
| 4 | Hsbc Holdings | 307.88 Bn | -2,967.28 Bn | - |
| 5 | Morgan Stanley | 298.41 Bn | -244.41 Bn | - |
| 6 | Royal Bank Of Canada | 283.46 Bn | -546.54 Bn | - |
| 7 | Goldman Sachs | 264.45 Bn | -3,478.99 Bn | - |
| 8 | Mitsubishi Ufj Financial | 259.19 Bn | -159.36 Bn | 5.24 Bn |
| 9 | Wells Fargo & Company | 258.28 Bn | 93.72 Bn | - |
| 10 | Magyar Bancorp | 142.06 Mn | 142.06 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 6.22 Mn |
| Jun 30, 2026 | 6.22 Mn |
| Mar 31, 2026 | 6.22 Mn |
| Dec 31, 2025 | 6.21 Mn |
| Sep 30, 2025 | 6.22 Mn |
| Jun 30, 2025 | 6.22 Mn |
| Mar 31, 2025 | 6.22 Mn |
| Dec 31, 2024 | 6.23 Mn |
| Sep 30, 2024 | 6.34 Mn |
| Jun 30, 2024 | 6.34 Mn |
| Mar 31, 2024 | 6.37 Mn |
| Dec 31, 2023 | 6.39 Mn |
| Sep 30, 2023 | 6.42 Mn |
| Jun 30, 2023 | 6.41 Mn |
| Mar 31, 2023 | 6.43 Mn |
| Dec 31, 2022 | 6.46 Mn |
| Sep 30, 2022 | 6.78 Mn |
| Jun 30, 2022 | 6.80 Mn |
| Mar 31, 2022 | 6.80 Mn |
| Dec 31, 2021 | 6.79 Mn |
API Access
Magyar Bancorp Weighted Average Shares Outstanding 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=weighted-average-shares-outstanding&ticker=MGYR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "weighted-average-shares-outstanding", "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=weighted-average-shares-outstanding&ticker=MGYR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();