Jones Lang Lasalle (JLL) Change in Accured Expenses (2009 - 2026)
Jones Lang Lasalle (JLL) reported Change in Accured Expenses of $10.1 million for Q2 2026, compared with -$38 million a year earlier.
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Analysis
Jones Lang Lasalle (JLL) Change in Accured Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Jones Lang Lasalle's Change in Accured Expenses came in at $186.4 million, up 902.2% year-over-year; for FY2025, it was $130.1 million, down 0.3% from FY2024.
- By year, Change in Accured Expenses came in at $130.5 million in FY2024 (+66.2%), $78.5 million in FY2023, -$283.3 million in FY2022 and $593.7 million in FY2021.
- Five-year quarterly Change in Accured Expenses spans a low of -$710.1 million in Q1 2022 and a high of $865.4 million in Q4 2021.
- Year over year, Change in Accured Expenses gained in two of the last four quarters, with growth averaging 8.9%.
- The high point for year-over-year Change in Accured Expenses in five years was Q4 2021 (growth of 156.5%); the low point was Q4 2022 (a decline of 75.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at -$642.3 million (Q1 2026), $575.2 million (Q4 2025) and $243.4 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Cbre | 37.56 Bn | 31.32 Bn | 2.09 Bn | 138.00 Mn |
| 2 | KE Holdings | 36.95 Bn | 17.65 Bn | 1.03 Bn | - |
| 3 | Jones Lang Lasalle | 14.12 Bn | 12.33 Bn | - | 10.10 Mn |
| 4 | Compass | 6.95 Bn | 5.41 Bn | - | -63.00 Mn |
| 5 | Colliers International | 4.59 Bn | 3.66 Bn | 635.11 Mn | 85.81 Mn |
| 6 | Cushman & Wakefield | 2.80 Bn | 278.27 Mn | 512.00 Mn | -25.90 Mn |
| 7 | Newmark | 2.01 Bn | 1.39 Bn | - | 2.95 Mn |
| 8 | Marcus & Millichap | 1.08 Bn | 178.91 Mn | - | 5.31 Mn |
| 9 | Agnt | 609.98 Mn | 139.66 Mn | 98.80 Mn | 36.44 Mn |
| 10 | Rmr | 568.78 Mn | 493.24 Mn | - | 11.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 10.10 Mn |
| Mar 31, 2026 | -642.30 Mn |
| Dec 31, 2025 | 575.20 Mn |
| Sep 30, 2025 | 243.40 Mn |
| Jun 30, 2025 | -38.00 Mn |
| Mar 31, 2025 | -650.50 Mn |
| Dec 31, 2024 | 457.90 Mn |
| Sep 30, 2024 | 249.20 Mn |
| Jun 30, 2024 | 22.50 Mn |
| Mar 31, 2024 | -599.10 Mn |
| Dec 31, 2023 | 507.30 Mn |
| Sep 30, 2023 | 204.40 Mn |
| Jun 30, 2023 | 18.60 Mn |
| Mar 31, 2023 | -651.80 Mn |
| Dec 31, 2022 | 208.70 Mn |
| Sep 30, 2022 | 181.60 Mn |
| Jun 30, 2022 | 36.50 Mn |
| Mar 31, 2022 | -710.10 Mn |
| Dec 31, 2021 | 865.40 Mn |
| Sep 30, 2021 | -6.00 Mn |
API Access
Jones Lang Lasalle Change in Accured 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=change-in-accured-expenses&ticker=JLL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-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=change-in-accured-expenses&ticker=JLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();