Jones Lang Lasalle (JLL) Cash & Equivalents (2009 - 2026)
Jones Lang Lasalle's Cash & Equivalents was $458.2 million in Q2 2026, up 14.2% from $401.4 million a year earlier and up 5.0% from the prior quarter.
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Analysis
Jones Lang Lasalle (JLL) Cash & Equivalents (2009 - 2026) Analysis & Trends
At the end of FY2025, Cash & Equivalents at Jones Lang Lasalle came in at $599.1 million, up 43.9% from FY2024.
- Cash & Equivalents shows a five-year compound annual growth rate of 0.8% (FY2020 to FY2025).
- In earlier years, Cash & Equivalents was $416.3 million in FY2024 (+1.5%), $410 million in FY2023 (-21.0%), $519.3 million in FY2022 (-12.5%) and $593.7 million in FY2021 (+3.4%).
- Quarterly Cash & Equivalents has moved between $389.5 million (Q3 2023) and $599.1 million (Q4 2025) over five years.
- Compared with a year earlier, Cash & Equivalents has increased for three straight quarters, with growth averaging 9.3% over the last eight quarters.
- The best year-over-year quarter for Cash & Equivalents over five years was Q4 2025 (growth of 43.9%); the worst was Q2 2023 (a decline of 29.1%).
- Per Business Quant data, JLL's Cash & Equivalents in the three quarters before Q2 2026 was $436.2 million (Q1 2026), $599.1 million (Q4 2025) and $428.9 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Cbre | 37.56 Bn | 31.32 Bn | 2.09 Bn | 1.49 Bn |
| 2 | KE Holdings | 36.95 Bn | 17.65 Bn | 1.03 Bn | 1.08 Bn |
| 3 | Jones Lang Lasalle | 14.12 Bn | 12.33 Bn | - | 458.20 Mn |
| 4 | Compass | 6.95 Bn | 5.41 Bn | - | 694.00 Mn |
| 5 | Colliers International | 4.59 Bn | 3.66 Bn | 635.11 Mn | 265.19 Mn |
| 6 | Cushman & Wakefield | 2.80 Bn | 278.27 Mn | 512.00 Mn | 500.50 Mn |
| 7 | Newmark | 2.01 Bn | 1.39 Bn | - | 259.70 Mn |
| 8 | Marcus & Millichap | 1.08 Bn | 178.91 Mn | - | 153.52 Mn |
| 9 | Agnt | 609.98 Mn | 139.66 Mn | 98.80 Mn | 111.16 Mn |
| 10 | Rmr | 568.78 Mn | 493.24 Mn | - | 58.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 458.20 Mn |
| Mar 31, 2026 | 436.20 Mn |
| Dec 31, 2025 | 599.10 Mn |
| Sep 30, 2025 | 428.90 Mn |
| Jun 30, 2025 | 401.40 Mn |
| Mar 31, 2025 | 432.40 Mn |
| Dec 31, 2024 | 416.30 Mn |
| Sep 30, 2024 | 437.80 Mn |
| Jun 30, 2024 | 424.40 Mn |
| Mar 31, 2024 | 396.70 Mn |
| Dec 31, 2023 | 410.00 Mn |
| Sep 30, 2023 | 389.50 Mn |
| Jun 30, 2023 | 402.50 Mn |
| Mar 31, 2023 | 485.40 Mn |
| Dec 31, 2022 | 519.30 Mn |
| Sep 30, 2022 | 489.40 Mn |
| Jun 30, 2022 | 568.00 Mn |
| Mar 31, 2022 | 575.80 Mn |
| Dec 31, 2021 | 593.70 Mn |
| Sep 30, 2021 | 535.90 Mn |
API Access
Jones Lang Lasalle Cash & Equivalents 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=cash-and-equivalents&ticker=JLL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "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=cash-and-equivalents&ticker=JLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();