Jones Lang Lasalle (JLL) Non Operating Interest Expenses (2009 - 2015)
Jones Lang Lasalle (JLL) posted Non Operating Interest Expenses of $7.76 million for Q4 2015, up 16.5% from $6.66 million a year earlier and up 14.5% from the prior quarter.
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Analysis
Jones Lang Lasalle (JLL) Non Operating Interest Expenses (2009 - 2015) Analysis & Trends
For FY2015, Jones Lang Lasalle's Non Operating Interest Expenses came in at $28.13 million, down 0.7% from FY2014.
- Annual Non Operating Interest Expenses has declined for six consecutive years, with a five-year compound annual growth rate of -9.3% (FY2010 to FY2015).
- In prior years, Jones Lang Lasalle's Non Operating Interest Expenses was $28.32 million in FY2014 (-18.4%), $34.72 million in FY2013 (-1.3%), $35.17 million in FY2012 (-1.2%) and $35.59 million in FY2011 (-22.3%).
- The Q4 2015 figure stands as the highest quarterly Non Operating Interest Expenses since Q4 2013.
- On a year-over-year basis, Non Operating Interest Expenses increased in 1 of the last eight quarters, with an average decline of 9.4%.
- The strongest year-over-year quarter for Non Operating Interest Expenses in the past five years was Q4 2012, with growth of 23.4%; the weakest was Q1 2011, with a decline of 29.7%.
- According to Business Quant data, Non Operating Interest Expenses for the three prior quarters was $6.77 million (Q3 2015), $7.56 million (Q2 2015) and $6.04 million (Q1 2015).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | KE Holdings | 37.89 Bn | 18.60 Bn | 1.03 Bn | - |
| 2 | Cbre | 37.24 Bn | 31.01 Bn | 2.09 Bn | - |
| 3 | Jones Lang Lasalle | 14.06 Bn | 12.27 Bn | - | - |
| 4 | Compass | 6.70 Bn | 5.16 Bn | - | 41.00 Mn |
| 5 | Colliers International | 4.59 Bn | 3.66 Bn | 635.11 Mn | - |
| 6 | Cushman & Wakefield | 2.77 Bn | 247.78 Mn | 512.00 Mn | 59.60 Mn |
| 7 | Newmark | 1.95 Bn | 1.33 Bn | - | - |
| 8 | Marcus & Millichap | 1.08 Bn | 173.61 Mn | - | 140,000.00 |
| 9 | Agnt | 613.32 Mn | 143.01 Mn | 98.80 Mn | - |
| 10 | Rmr | 580.01 Mn | 504.47 Mn | - | 3.21 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2015 | 7.76 Mn |
| Sep 30, 2015 | 6.77 Mn |
| Jun 30, 2015 | 7.56 Mn |
| Mar 31, 2015 | 6.04 Mn |
| Dec 31, 2014 | 6.66 Mn |
| Sep 30, 2014 | 7.36 Mn |
| Jun 30, 2014 | 7.66 Mn |
| Mar 31, 2014 | 6.64 Mn |
| Dec 31, 2013 | 8.12 Mn |
| Sep 30, 2013 | 9.63 Mn |
| Jun 30, 2013 | 9.05 Mn |
| Mar 31, 2013 | 7.92 Mn |
| Dec 31, 2012 | 10.34 Mn |
| Sep 30, 2012 | 9.95 Mn |
| Jun 30, 2012 | 7.46 Mn |
| Mar 31, 2012 | 7.43 Mn |
| Dec 31, 2011 | 8.37 Mn |
| Sep 30, 2011 | 9.67 Mn |
| Jun 30, 2011 | 9.59 Mn |
| Mar 31, 2011 | 7.96 Mn |
API Access
Jones Lang Lasalle Non Operating Interest Expenses 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=non-operating-interest-expenses&ticker=JLL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "JLL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=non-operating-interest-expenses&ticker=JLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();