Jones Lang Lasalle (JLL) Other Accumulated Expenses (2009 - 2026)
Jones Lang Lasalle (JLL) recorded Other Accumulated Expenses of $274.4 million in Q2 2026, down 16.7% from $329.6 million a year earlier but up 3.7% from the prior quarter.
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Analysis
Jones Lang Lasalle (JLL) Other Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Jones Lang Lasalle reported Other Accumulated Expenses of $263.8 million, down 18.0% from FY2024.
- Annual Other Accumulated Expenses has a five-year compound annual growth rate of -2.5% (FY2020 to FY2025).
- Across earlier years, Other Accumulated Expenses came in at $321.9 million in FY2024 (-6.8%), $345.3 million in FY2023 (+4.5%), $330.5 million in FY2022 (+51.5%) and $218.1 million in FY2021 (-27.2%).
- Quarterly Other Accumulated Expenses has ranged from $218.1 million in Q4 2021 to $464.8 million in Q3 2023 over the past five years.
- On a year-over-year basis, Other Accumulated Expenses has declined for ten consecutive quarters, with an average decline of 13.6% over the last eight quarters.
- Peak year-over-year performance for Other Accumulated Expenses in the last five years was growth of 60.4% in Q3 2022, against a decline of 27.2% in Q4 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $264.7 million (Q1 2026), $263.8 million (Q4 2025) and $308.5 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Cbre | 37.56 Bn | 31.32 Bn | 2.09 Bn |
| 2 | KE Holdings | 36.95 Bn | 17.65 Bn | 1.03 Bn |
| 3 | Jones Lang Lasalle | 14.12 Bn | 12.33 Bn | - |
| 4 | Compass | 6.95 Bn | 5.41 Bn | - |
| 5 | Colliers International | 4.59 Bn | 3.66 Bn | 635.11 Mn |
| 6 | Cushman & Wakefield | 2.80 Bn | 278.27 Mn | 512.00 Mn |
| 7 | Newmark | 2.01 Bn | 1.39 Bn | - |
| 8 | Marcus & Millichap | 1.08 Bn | 178.91 Mn | - |
| 9 | Agnt | 609.98 Mn | 139.66 Mn | 98.80 Mn |
| 10 | Rmr | 568.78 Mn | 493.24 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 274.40 Mn |
| Mar 31, 2026 | 264.70 Mn |
| Dec 31, 2025 | 263.80 Mn |
| Sep 30, 2025 | 308.50 Mn |
| Jun 30, 2025 | 329.60 Mn |
| Mar 31, 2025 | 294.00 Mn |
| Dec 31, 2024 | 321.90 Mn |
| Sep 30, 2024 | 339.20 Mn |
| Jun 30, 2024 | 360.80 Mn |
| Mar 31, 2024 | 337.50 Mn |
| Dec 31, 2023 | 345.30 Mn |
| Sep 30, 2023 | 464.80 Mn |
| Jun 30, 2023 | 412.40 Mn |
| Mar 31, 2023 | 377.20 Mn |
| Dec 31, 2022 | 330.50 Mn |
| Sep 30, 2022 | 380.70 Mn |
| Jun 30, 2022 | 269.40 Mn |
| Mar 31, 2022 | 274.40 Mn |
| Dec 31, 2021 | 218.10 Mn |
| Sep 30, 2021 | 237.40 Mn |
API Access
Jones Lang Lasalle Other Accumulated 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=other-accumulated-expenses&ticker=JLL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-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=other-accumulated-expenses&ticker=JLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();