Cme (CME) Rent Expense (2009 - 2018)
Cme (CME) recorded Rent Expense of $21 million in Q3 2018, up 6.1% from $19.8 million a year earlier and up 4.0% from the prior quarter.
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Analysis
Cme (CME) Rent Expense (2009 - 2018) Analysis & Trends
On a TTM basis, Cme's Rent Expense came in at $82.3 million as of Sep 30, 2018, up 2.2% year-over-year; for FY2017, it was $80.2 million, down 7.5% from FY2016.
- Annual Rent Expense has declined for three straight years, though with a five-year compound annual growth rate of 0.8% (FY2012 to FY2017).
- Across earlier years, Rent Expense came in at $86.7 million in FY2016 (-6.3%), $92.5 million in FY2015 (-4.4%), $96.8 million in FY2014 (+23.6%) and $78.3 million in FY2013 (+1.7%).
- Quarterly Rent Expense has ranged from $19.2 million in Q2 2017 to $25.7 million in Q4 2014 over the past five years.
- On a year-over-year basis, Rent Expense rose in three of the last eight quarters, with an average decline of 3.0%.
- Peak year-over-year performance for Rent Expense in the last five years was growth of 28.6% in Q3 2014, against a decline of 21.3% in Q2 2017 at the low end.
- Per Business Quant, the preceding three quarters came in at $20.2 million (Q2 2018), $20 million (Q1 2018) and $21.1 million (Q4 2017).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Rental Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 104.70 Bn | 85.79 Bn | - | - |
| 2 | Bank of New York Mellon | 100.72 Bn | 40.09 Bn | - | 143.00 Mn |
| 3 | Cme | 94.58 Bn | 94.58 Bn | - | - |
| 4 | Intercontinental Exchange | 85.83 Bn | 79.63 Bn | - | 23.00 Mn |
| 5 | Nasdaq | 52.05 Bn | 49.49 Bn | 1.50 Bn | 35.00 Mn |
| 6 | State Street | 49.39 Bn | 49.39 Bn | - | 96.00 Mn |
| 7 | Interactive Brokers | 39.24 Bn | 32.69 Bn | - | - |
| 8 | Northern Trust | 31.94 Bn | 31.94 Bn | - | 53.50 Mn |
| 9 | Cboe Global Markets | 26.47 Bn | 18.13 Bn | 731.60 Mn | 6.10 Mn |
| 10 | LPL Financial Holdings | 24.62 Bn | 19.94 Bn | - | 125.54 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2018 | 21.00 Mn |
| Jun 30, 2018 | 20.20 Mn |
| Mar 31, 2018 | 20.00 Mn |
| Dec 31, 2017 | 21.10 Mn |
| Sep 30, 2017 | 19.80 Mn |
| Jun 30, 2017 | 19.20 Mn |
| Mar 31, 2017 | 20.10 Mn |
| Dec 31, 2016 | 21.40 Mn |
| Sep 30, 2016 | 19.60 Mn |
| Jun 30, 2016 | 24.40 Mn |
| Mar 31, 2016 | 21.30 Mn |
| Dec 31, 2015 | 23.10 Mn |
| Sep 30, 2015 | 23.10 Mn |
| Jun 30, 2015 | 23.50 Mn |
| Mar 31, 2015 | 22.80 Mn |
| Dec 31, 2014 | 25.70 Mn |
| Sep 30, 2014 | 24.70 Mn |
| Jun 30, 2014 | 23.20 Mn |
| Mar 31, 2014 | 23.20 Mn |
| Dec 31, 2013 | 21.60 Mn |
API Access
Cme Rent 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=rent-expense&ticker=CME&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "rent-expense", "ticker": "CME", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=rent-expense&ticker=CME&period=max&api_key=YOUR_API_KEY");
const data = await res.json();