American Express (AXP) Occupancy Expense (2012 - 2019)
American Express (AXP) recorded Occupancy Expense of $508 million in Q1 2019, down 2.3% from $520 million a year earlier and down 5.9% from the prior quarter.
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Analysis
American Express (AXP) Occupancy Expense (2012 - 2019) Analysis & Trends
On a TTM basis, American Express' Occupancy Expense came in at $2.02 billion as of Mar 31, 2019, down 2.1% year-over-year; for FY2018, it was $2.03 billion, up 0.7% from FY2017.
- Annual Occupancy Expense has a five-year compound annual growth rate of 1.3% (FY2013 to FY2018).
- Across earlier years, Occupancy Expense came in at $2.02 billion in FY2017 (+9.9%), $1.84 billion in FY2016 (-0.9%), $1.85 billion in FY2015 (+2.6%) and $1.81 billion in FY2014 (-5.1%).
- Quarterly Occupancy Expense has ranged from -$25 million in Q4 2016 to $630 million in Q3 2016 over the past five years.
- On a year-over-year basis, Occupancy Expense rose in three of the last seven quarters, with growth averaging 0.5%.
- Peak year-over-year performance for Occupancy Expense in the last five years was growth of 21.1% in Q3 2015, against a decline of 13.8% in Q3 2018 at the low end.
- Per Business Quant, the preceding three quarters came in at $540 million (Q4 2018), $489 million (Q3 2018) and $484 million (Q2 2018).
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 | American Express | 215.12 Bn | 14.60 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2019 | 508.00 Mn |
| Dec 31, 2018 | 540.00 Mn |
| Sep 30, 2018 | 489.00 Mn |
| Jun 30, 2018 | 484.00 Mn |
| Mar 31, 2018 | 520.00 Mn |
| Dec 31, 2017 | 493.00 Mn |
| Sep 30, 2017 | 567.00 Mn |
| Jun 30, 2017 | 484.00 Mn |
| Mar 31, 2017 | 474.00 Mn |
| Dec 31, 2016 | -25.00 Mn |
| Sep 30, 2016 | 630.00 Mn |
| Jun 30, 2016 | 438.00 Mn |
| Mar 31, 2016 | 465.00 Mn |
| Dec 31, 2015 | 482.00 Mn |
| Sep 30, 2015 | 523.00 Mn |
| Jun 30, 2015 | 415.00 Mn |
| Mar 31, 2015 | 434.00 Mn |
| Dec 31, 2014 | 446.00 Mn |
| Sep 30, 2014 | 432.00 Mn |
| Jun 30, 2014 | 467.00 Mn |
API Access
American Express Occupancy Expense 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=occupancy-expense&ticker=AXP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "occupancy-expense", "ticker": "AXP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=occupancy-expense&ticker=AXP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();