Vivmark Residential (VMRK) Total Operating Expenses (2009 - 2026)
Vivmark Residential (VMRK) posted Operating Expenses of $2.06 billion for Q3 2026, up 235.0% from $615.14 million a year earlier and up 264.0% from the prior quarter.
Vivmark Residential (VMRK) Total Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Sep 30, 2026, Operating Expenses at Vivmark Residential was $3.63 billion, up 59.1% year-over-year; for FY2025, it was $2.22 billion, up 5.5% from FY2024.
- Annual Operating Expenses has increased for five consecutive years, with a five-year compound annual growth rate of 4.5% (FY2020 to FY2025).
- In prior years, Vivmark Residential's Operating Expenses was $2.11 billion in FY2024 (+5.6%), $2 billion in FY2023 (+3.8%), $1.92 billion in FY2022 (+4.3%) and $1.84 billion in FY2021 (+3.3%).
- The Q3 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q1 2009.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 32.9%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2026, with growth of 235.0%; the weakest was Q4 2025, with a decline of 21.9%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $566.18 million (Q2 2026), $566.18 million (Q1 2026) and $432.96 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Welltower | 179.36 Bn | 166.43 Bn | 1.47 Bn |
| 2 | Prologis | 122.34 Bn | 120.73 Bn | - |
| 3 | Simon Property | 79.95 Bn | 78.05 Bn | - |
| 4 | Public Storage | 62.14 Bn | 61.58 Bn | 112.08 Mn |
| 5 | Realty Income | 55.95 Bn | 57.33 Bn | - |
| 6 | Ventas | 47.02 Bn | 46.18 Bn | -3.39 Bn |
| 7 | Ryman Hospitality Properties | 46.62 Bn | 45.46 Bn | 266.41 Mn |
| 8 | Vivmark Residential | 37.34 Bn | 37.09 Bn | - |
| 9 | Extra Space Storage | 33.12 Bn | 32.90 Bn | 650.96 Mn |
| 10 | Vici Properties | 27.54 Bn | 26.32 Bn | 1.06 Bn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 2.06 Bn |
| Jun 30, 2026 | 566.18 Mn |
| Mar 31, 2026 | 566.18 Mn |
| Dec 31, 2025 | 432.96 Mn |
| Sep 30, 2025 | 615.14 Mn |
| Jun 30, 2025 | 542.81 Mn |
| Mar 31, 2025 | 566.54 Mn |
| Dec 31, 2024 | 554.28 Mn |
| Sep 30, 2024 | 525.09 Mn |
| Jun 30, 2024 | 508.61 Mn |
| Mar 31, 2024 | 520.43 Mn |
| Dec 31, 2023 | 490.50 Mn |
| Sep 30, 2023 | 498.94 Mn |
| Jun 30, 2023 | 498.76 Mn |
| Mar 31, 2023 | 507.71 Mn |
| Dec 31, 2022 | 457.32 Mn |
| Sep 30, 2022 | 477.64 Mn |
| Jun 30, 2022 | 484.99 Mn |
| Mar 31, 2022 | 503.51 Mn |
| Dec 31, 2021 | 471.04 Mn |
Vivmark Residential Total 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=total-operating-expenses&ticker=VMRK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-operating-expenses", "ticker": "VMRK", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-operating-expenses&ticker=VMRK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();