Hancock Whitney (HWC) Cash Due from Bank (2009 - 2017)
Hancock Whitney's Cash Due from Bank came in at $386.95 million for Q4 2017, up 3.8% from $372.69 million a year earlier and up 15.9% from the prior quarter.
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Analysis
Hancock Whitney (HWC) Cash Due from Bank (2009 - 2017) Analysis & Trends
Going back to Q4 2009, Hancock Whitney's Cash Due from Bank data covers 26 quarters.
- Cash Due from Bank carries a five-year compound annual growth rate of -2.9% (FY2012 to FY2017).
- Going back by year, Cash Due from Bank was $372.69 million in FY2016 (+22.6%), $303.87 million in FY2015 (-14.8%), $356.46 million in FY2014 (+2.3%) and $348.44 million in FY2013 (-22.3%).
- The Q4 2017 figure represents the highest quarterly Cash Due from Bank since Q4 2012.
- Year-over-year, Cash Due from Bank has increased for six consecutive quarters, with growth averaging 5.4% over the last eight quarters.
- The fastest year-over-year change in Cash Due from Bank over five years came in Q4 2016 (growth of 22.6%), and the weakest in Q4 2013 (a decline of 22.3%).
- Business Quant data shows HWC's Cash Due from Bank at $333.78 million (Q3 2017), $365.23 million (Q2 2017) and $333.31 million (Q1 2017) in the three quarters before Q4 2017.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash Due from Bank (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 883.45 Bn | 912.92 Bn | - | 24.72 Bn |
| 2 | Banco Santander Chile | 401.52 Bn | 521.46 Bn | - | - |
| 3 | Bank Of America | 377.43 Bn | -1,998.64 Bn | - | 28.10 Bn |
| 4 | Hsbc Holdings | 330.31 Bn | 330.37 Bn | - | - |
| 5 | Morgan Stanley | 299.17 Bn | -209.92 Bn | - | - |
| 6 | Royal Bank Of Canada | 274.08 Bn | 124.82 Bn | - | 46.00 Bn |
| 7 | Mitsubishi Ufj Financial | 270.70 Bn | -1,317.79 Bn | 10.89 Bn | 505.89 Bn |
| 8 | Goldman Sachs | 263.13 Bn | -3,293.98 Bn | - | - |
| 9 | Wells Fargo & Company | 243.64 Bn | 245.78 Bn | - | 42.16 Bn |
| 10 | Hancock Whitney | 5.88 Bn | 3.68 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2017 | 386.95 Mn |
| Sep 30, 2017 | 333.78 Mn |
| Jun 30, 2017 | 365.23 Mn |
| Mar 31, 2017 | 333.31 Mn |
| Dec 31, 2016 | 372.69 Mn |
| Sep 30, 2016 | 329.87 Mn |
| Jun 30, 2016 | 313.43 Mn |
| Mar 31, 2016 | 291.10 Mn |
| Dec 31, 2015 | 303.87 Mn |
| Sep 30, 2015 | 323.74 Mn |
| Jun 30, 2015 | 329.61 Mn |
| Mar 31, 2015 | 333.74 Mn |
| Dec 31, 2014 | 356.46 Mn |
| Dec 31, 2013 | 348.44 Mn |
| Dec 31, 2012 | 448.49 Mn |
| Jun 30, 2012 | 392.60 Mn |
| Mar 31, 2012 | 357.81 Mn |
| Dec 31, 2011 | 437.95 Mn |
| Sep 30, 2011 | 373.69 Mn |
| Jun 30, 2011 | 381.33 Mn |
API Access
Hancock Whitney Cash Due from Bank 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=cash-due-from-bank&ticker=HWC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-due-from-bank", "ticker": "HWC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=cash-due-from-bank&ticker=HWC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();