Ventas (VTR) Non Operating Interest Expenses (2009 - 2026)
Ventas' Non Operating Interest Expenses was $160.03 million in Q2 2026, up 6.5% from $150.3 million a year earlier and up 2.5% from the prior quarter.
Ventas (VTR) Non Operating Interest Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Ventas' Non Operating Interest Expenses was $628.77 million through Jun 30, 2026, up 4.2% year-over-year; for FY2025, it was $612.25 million, up 1.6% from FY2024.
- Non Operating Interest Expenses has now increased for four consecutive years, with a five-year compound annual growth rate of 5.5% (FY2020 to FY2025).
- In earlier years, Non Operating Interest Expenses was $602.84 million in FY2024 (+5.0%), $574.11 million in FY2023 (+22.8%), $467.56 million in FY2022 (+6.2%) and $440.09 million in FY2021 (-6.3%).
- The Q2 2026 figure marks the highest quarterly Non Operating Interest Expenses in data going back to Q1 2009.
- Compared with a year earlier, Non Operating Interest Expenses has increased for five straight quarters, with growth averaging 2.2% over the last eight quarters.
- The best year-over-year quarter for Non Operating Interest Expenses over five years was Q2 2023 (growth of 25.7%); the worst was Q3 2021 (a decline of 5.8%).
- Per Business Quant data, VTR's Non Operating Interest Expenses in the three quarters before Q2 2026 was $156.14 million (Q1 2026), $154.47 million (Q4 2025) and $158.12 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 166.01 Bn | 148.52 Bn | 1.39 Bn | - |
| 2 | Prologis | 121.16 Bn | 125.55 Bn | - | 276.31 Mn |
| 3 | Simon Property | 65.49 Bn | 66.75 Bn | - | 272.33 Mn |
| 4 | Realty Income | 51.38 Bn | 53.76 Bn | - | - |
| 5 | Public Storage | 49.67 Bn | 48.75 Bn | - | 84.78 Mn |
| 6 | Ventas | 43.61 Bn | 42.81 Bn | - | 160.03 Mn |
| 7 | Extra Space Storage | 27.79 Bn | 27.79 Bn | 642.43 Mn | - |
| 8 | Vici Properties | 25.29 Bn | 23.41 Bn | 1.05 Bn | 209.93 Mn |
| 9 | Vivmark Residential | 22.78 Bn | 22.97 Bn | - | 82.46 Mn |
| 10 | Invitation Homes | 15.55 Bn | 15.59 Bn | - | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 160.03 Mn |
| Mar 31, 2026 | 156.14 Mn |
| Dec 31, 2025 | 154.47 Mn |
| Sep 30, 2025 | 158.12 Mn |
| Jun 30, 2025 | 150.30 Mn |
| Mar 31, 2025 | 149.36 Mn |
| Dec 31, 2024 | 153.21 Mn |
| Sep 30, 2024 | 150.44 Mn |
| Jun 30, 2024 | 149.26 Mn |
| Mar 31, 2024 | 149.93 Mn |
| Dec 31, 2023 | 154.85 Mn |
| Sep 30, 2023 | 147.92 Mn |
| Jun 30, 2023 | 143.27 Mn |
| Mar 31, 2023 | 128.08 Mn |
| Dec 31, 2022 | 123.40 Mn |
| Sep 30, 2022 | 119.41 Mn |
| Jun 30, 2022 | 113.95 Mn |
| Mar 31, 2022 | 110.79 Mn |
| Dec 31, 2021 | 110.46 Mn |
| Sep 30, 2021 | 108.82 Mn |
Ventas Non Operating Interest 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=non-operating-interest-expenses&ticker=VTR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "VTR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=non-operating-interest-expenses&ticker=VTR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();