Magyar Bancorp (MGYR) Loans - Net (2009 - 2023)
Magyar Bancorp's Loans - Net was $693.31 million in fiscal Q3 2023 (quarter ended Jun 30, 2023), up 12.4% from $616.66 million a year earlier and up 3.9% from the prior quarter.
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Analysis
Magyar Bancorp (MGYR) Loans - Net (2009 - 2023) Analysis & Trends
At the end of FY2022 (ended Sep 30, 2022), Loans - Net at Magyar Bancorp came in at $619.84 million, up 5.9% from FY2021.
- Loans - Net shows a five-year compound annual growth rate of 5.7% (FY2017 to FY2022).
- In earlier fiscal years, Loans - Net was $585.3 million in FY2021 (-3.0%), $603.11 million in FY2020 (+16.4%), $518.22 million in FY2019 (+1.9%) and $508.43 million in FY2018 (+8.0%).
- The fiscal Q3 2023 figure marks the highest quarterly Loans - Net in data going back to fiscal Q4 2010.
- Compared with a year earlier, Loans - Net has increased for five straight quarters, with growth averaging 4.7% over the last eight quarters.
- The best year-over-year quarter for Loans - Net over five years was fiscal Q4 2020 (growth of 16.4%); the worst was fiscal Q1 2022 (a decline of 4.1%).
- Per Business Quant data, MGYR's Loans - Net in the three fiscal quarters before Q3 2023 was $667.27 million (Q2 2023), $666.08 million (Q1 2023) and $619.84 million (Q4 2022).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Loans - Net (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 920.14 Bn | 897.90 Bn | - | 1,558.37 Bn |
| 2 | Banco Santander Chile | 407.42 Bn | -7,109.68 Bn | - | - |
| 3 | Bank Of America | 353.20 Bn | -2,022.91 Bn | - | 1,238.26 Bn |
| 4 | Hsbc Holdings | 307.88 Bn | -2,967.28 Bn | - | 1,029.86 Bn |
| 5 | Morgan Stanley | 298.41 Bn | -244.41 Bn | - | 297.21 Bn |
| 6 | Royal Bank Of Canada | 283.46 Bn | -546.54 Bn | - | 791.32 Bn |
| 7 | Goldman Sachs | 264.45 Bn | -3,478.99 Bn | - | 275.65 Bn |
| 8 | Mitsubishi Ufj Financial | 259.19 Bn | -159.36 Bn | 5.24 Bn | - |
| 9 | Wells Fargo & Company | 258.28 Bn | 93.72 Bn | - | 1,034.29 Bn |
| 10 | Magyar Bancorp | 142.06 Mn | 142.06 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2023 | 693.31 Mn |
| Mar 31, 2023 | 667.27 Mn |
| Dec 31, 2022 | 666.08 Mn |
| Sep 30, 2022 | 619.84 Mn |
| Jun 30, 2022 | 616.66 Mn |
| Mar 31, 2022 | 609.41 Mn |
| Dec 31, 2021 | 574.27 Mn |
| Sep 30, 2021 | 585.30 Mn |
| Jun 30, 2021 | 605.57 Mn |
| Mar 31, 2021 | 616.98 Mn |
| Dec 31, 2020 | 598.53 Mn |
| Sep 30, 2020 | 603.11 Mn |
| Jun 30, 2020 | 604.55 Mn |
| Mar 31, 2020 | 541.92 Mn |
| Dec 31, 2019 | 525.43 Mn |
| Sep 30, 2019 | 518.22 Mn |
| Jun 30, 2019 | 526.28 Mn |
| Mar 31, 2019 | 515.38 Mn |
| Dec 31, 2018 | 510.16 Mn |
| Sep 30, 2018 | 508.43 Mn |
API Access
Magyar Bancorp Loans - Net 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=loans-net&ticker=MGYR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "loans-net", "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=loans-net&ticker=MGYR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();