Newmark (NMRK) Operating Expenses (2017 - 2026)
Newmark (NMRK) posted Operating Expenses of $848.02 million for Q2 2026, up 18.3% from $716.6 million a year earlier and up 3.4% from the prior quarter.
Newmark (NMRK) Operating Expenses (2017 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Newmark was $3.37 billion, up 19.7% year-over-year; for FY2025, it came in at $3.1 billion, up 20.2% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 12.3% (FY2020 to FY2025).
- In prior years, Newmark's Operating Expenses was $2.58 billion in FY2024 (+9.5%), $2.36 billion in FY2023 (-2.6%), $2.42 billion in FY2022 (-16.0%) and $2.88 billion in FY2021 (+66.1%).
- Quarterly Operating Expenses has run from a low of $529.6 million in Q1 2023 to a high of $882.39 million in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last 11 quarters, with growth averaging 17.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2021, with growth of 65.4%; the weakest was Q2 2022, with a decline of 33.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $820.2 million (Q1 2026), $882.39 million (Q4 2025) and $820.33 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | KE Holdings | 38.10 Bn | 18.80 Bn | 1.03 Bn | -587.69 Mn |
| 2 | Cbre | 37.79 Bn | 31.56 Bn | 2.09 Bn | - |
| 3 | Jones Lang Lasalle | 14.45 Bn | 12.66 Bn | - | 6.64 Bn |
| 4 | Compass | 6.85 Bn | 5.32 Bn | - | 4.18 Bn |
| 5 | Colliers International | 4.59 Bn | 3.67 Bn | 635.11 Mn | 485.10 Mn |
| 6 | Cushman & Wakefield | 2.78 Bn | 264.20 Mn | 512.00 Mn | 2.63 Bn |
| 7 | Newmark | 1.99 Bn | 1.37 Bn | - | 848.02 Mn |
| 8 | Marcus & Millichap | 1.10 Bn | 194.81 Mn | - | 200.70 Mn |
| 9 | Rmr | 593.80 Mn | 518.26 Mn | - | 162.79 Mn |
| 10 | Agnt | 586.58 Mn | 116.27 Mn | 98.80 Mn | 97.16 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 848.02 Mn |
| Mar 31, 2026 | 820.20 Mn |
| Dec 31, 2025 | 882.39 Mn |
| Sep 30, 2025 | 820.33 Mn |
| Jun 30, 2025 | 716.60 Mn |
| Mar 31, 2025 | 683.76 Mn |
| Dec 31, 2024 | 769.57 Mn |
| Sep 30, 2024 | 645.18 Mn |
| Jun 30, 2024 | 598.29 Mn |
| Mar 31, 2024 | 569.10 Mn |
| Dec 31, 2023 | 677.74 Mn |
| Sep 30, 2023 | 589.44 Mn |
| Jun 30, 2023 | 562.23 Mn |
| Mar 31, 2023 | 529.60 Mn |
| Dec 31, 2022 | 585.66 Mn |
| Sep 30, 2022 | 606.03 Mn |
| Jun 30, 2022 | 650.91 Mn |
| Mar 31, 2022 | 579.66 Mn |
| Dec 31, 2021 | 800.71 Mn |
| Sep 30, 2021 | 665.28 Mn |
Newmark Operating 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=operating-expenses&ticker=NMRK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NMRK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=NMRK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();