First Busey (BUSE) Mortgage Banking (2016 - 2018)
First Busey's Mortgage Banking came in at $585,000 for Q4 2018, down 9.9% from $649,000 a year earlier but up 16.8% from the prior quarter.
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Analysis
First Busey (BUSE) Mortgage Banking (2016 - 2018) Analysis & Trends
For FY2018, First Busey's Mortgage Banking was $2.26 million, up 5.9% from FY2017.
- Going back by year, Mortgage Banking was $2.13 million in FY2017 (+18.3%) and $1.8 million in FY2016.
- The five-year range for quarterly Mortgage Banking is $395,000 (Q1 2017) to $649,000 (Q4 2017).
- Year-over-year, Mortgage Banking increased in five of the last seven quarters, with growth averaging 19.8%.
- Business Quant data shows BUSE's Mortgage Banking at $501,000 (Q3 2018), $552,000 (Q2 2018) and $617,000 (Q1 2018) in the three quarters before Q4 2018.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Jpmorgan Chase | 895.36 Bn | 924.83 Bn | - |
| 2 | Banco Santander Chile | 425.01 Bn | 544.95 Bn | - |
| 3 | Bank Of America | 389.22 Bn | -1,986.85 Bn | - |
| 4 | Hsbc Holdings | 347.56 Bn | 347.61 Bn | - |
| 5 | Morgan Stanley | 304.44 Bn | -204.66 Bn | - |
| 6 | Royal Bank Of Canada | 281.54 Bn | 132.29 Bn | - |
| 7 | Mitsubishi Ufj Financial | 277.23 Bn | -1,311.26 Bn | 10.89 Bn |
| 8 | Goldman Sachs | 267.12 Bn | -3,289.99 Bn | - |
| 9 | Wells Fargo & Company | 244.76 Bn | 246.90 Bn | - |
| 10 | First Busey | 2.48 Bn | 794.99 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2018 | 585,000.00 |
| Sep 30, 2018 | 501,000.00 |
| Jun 30, 2018 | 552,000.00 |
| Mar 31, 2018 | 617,000.00 |
| Dec 31, 2017 | 649,000.00 |
| Sep 30, 2017 | 583,000.00 |
| Jun 30, 2017 | 503,000.00 |
| Mar 31, 2017 | 395,000.00 |
| Dec 31, 2016 | 420,000.00 |
| Sep 30, 2016 | 447,000.00 |
| Jun 30, 2016 | 450,000.00 |
API Access
First Busey Mortgage Banking 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=mortgage-banking&ticker=BUSE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "mortgage-banking", "ticker": "BUSE", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=mortgage-banking&ticker=BUSE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();