Magyar Bancorp (MGYR) Professional Fees (2009 - 2026)
Magyar Bancorp's Professional Fees came in at $134,000 for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 30.9% from $194,000 a year earlier and down 23.0% from the prior quarter.
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Analysis
Magyar Bancorp (MGYR) Professional Fees (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Magyar Bancorp reported Professional Fees of $594,000, down 20.9% year-over-year; for FY2025 (ended Sep 30, 2025), it was $705,000, down 11.2% from FY2024.
- Professional Fees carries a five-year compound annual growth rate of -14.7% (FY2020 to FY2025).
- Going back by fiscal year, Professional Fees was $794,000 in FY2024 (+5.2%), $755,000 in FY2023 (-28.9%), $1.06 million in FY2022 (-38.2%) and $1.72 million in FY2021 (+10.3%).
- The five-year range for quarterly Professional Fees is $113,000 (fiscal Q4 2025) to $387,000 (fiscal Q1 2022).
- Year-over-year, Professional Fees increased in two of the last eight quarters, with an average decline of 12.2%.
- The fastest year-over-year change in Professional Fees over five years came in fiscal Q1 2024 (growth of 26.3%), and the weakest in fiscal Q1 2023 (a decline of 53.7%).
- Business Quant data shows MGYR's Professional Fees at $174,000 (Q2 2026), $173,000 (Q1 2026) and $113,000 (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Professional Fees (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 920.14 Bn | 897.90 Bn | - | 3.90 Bn |
| 2 | Banco Santander Chile | 407.42 Bn | -7,109.68 Bn | - | - |
| 3 | Bank Of America | 353.20 Bn | -2,022.91 Bn | - | 606.00 Mn |
| 4 | Hsbc Holdings | 307.88 Bn | -2,967.28 Bn | - | - |
| 5 | Morgan Stanley | 298.41 Bn | -244.41 Bn | - | 700.00 Mn |
| 6 | Royal Bank Of Canada | 283.46 Bn | -546.54 Bn | - | 411.67 Mn |
| 7 | Goldman Sachs | 264.45 Bn | -3,478.99 Bn | - | 424.00 Mn |
| 8 | Mitsubishi Ufj Financial | 259.19 Bn | -159.36 Bn | 5.24 Bn | - |
| 9 | Wells Fargo & Company | 258.28 Bn | 93.72 Bn | - | 1.17 Bn |
| 10 | Magyar Bancorp | 142.06 Mn | 142.06 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 134,000.00 |
| Mar 31, 2026 | 174,000.00 |
| Dec 31, 2025 | 173,000.00 |
| Sep 30, 2025 | 113,000.00 |
| Jun 30, 2025 | 194,000.00 |
| Mar 31, 2025 | 169,000.00 |
| Dec 31, 2024 | 199,000.00 |
| Sep 30, 2024 | 189,000.00 |
| Jun 30, 2024 | 200,000.00 |
| Mar 31, 2024 | 178,000.00 |
| Dec 31, 2023 | 226,000.00 |
| Sep 30, 2023 | 183,000.00 |
| Jun 30, 2023 | 188,000.00 |
| Mar 31, 2023 | 205,000.00 |
| Dec 31, 2022 | 179,000.00 |
| Sep 30, 2022 | 206,000.00 |
| Jun 30, 2022 | 198,000.00 |
| Mar 31, 2022 | 270,000.00 |
| Dec 31, 2021 | 387,000.00 |
| Sep 30, 2021 | 337,000.00 |
API Access
Magyar Bancorp Professional Fees 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=professional-fees&ticker=MGYR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "professional-fees", "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=professional-fees&ticker=MGYR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();