Copper Property CTL Pass Through Trust (CPPTL) Operating Expenses (2021 - 2026)
Copper Property CTL Pass Through Trust's Operating Expenses was $9.96 million in Q2 2026, up 14.5% from $8.7 million a year earlier but down 24.6% from the prior quarter.
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Analysis
Copper Property CTL Pass Through Trust (CPPTL) Operating Expenses (2021 - 2026) Analysis & Trends
On a trailing twelve-month basis, Copper Property CTL Pass Through Trust's Operating Expenses was $63.47 million through Jun 30, 2026, up 71.3% year-over-year; for FY2025, it came in at $57.91 million, up 53.4% from FY2024.
- Operating Expenses shows a four-year compound annual growth rate of -0.7% (FY2021 to FY2025).
- In earlier years, Operating Expenses was $37.75 million in FY2024 (+1.7%), $37.12 million in FY2023 (-14.3%), $43.3 million in FY2022 (-27.3%) and $59.54 million in FY2021.
- Quarterly Operating Expenses has moved between $8.68 million (Q3 2023) and $21.42 million (Q3 2025) over five years.
- Compared with a year earlier, Operating Expenses has increased for four straight quarters, with growth averaging 35.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2025 (growth of 116.9%); the worst was Q2 2022 (a decline of 36.4%).
- Per Business Quant data, CPPTL's Operating Expenses in the three quarters before Q2 2026 was $13.2 million (Q1 2026), $18.88 million (Q4 2025) and $21.42 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 167.95 Bn | 150.46 Bn | 1.39 Bn | 3.22 Bn |
| 2 | Prologis | 123.54 Bn | 127.93 Bn | - | 1.47 Bn |
| 3 | Simon Property | 66.76 Bn | 68.02 Bn | - | 900.79 Mn |
| 4 | Realty Income | 52.37 Bn | 54.76 Bn | - | 1.19 Bn |
| 5 | Public Storage | 50.03 Bn | 49.11 Bn | - | 766.20 Mn |
| 6 | Ventas | 44.65 Bn | 43.84 Bn | - | 1.68 Bn |
| 7 | Extra Space Storage | 27.81 Bn | 27.81 Bn | 642.43 Mn | 481.97 Mn |
| 8 | Vici Properties | 25.53 Bn | 23.65 Bn | 1.05 Bn | 315.61 Mn |
| 9 | Vivmark Residential | 23.01 Bn | 23.20 Bn | - | 566.18 Mn |
| 10 | Copper Property CTL Pass Through Trust | 765.00 Mn | 765.00 Mn | - | 9.96 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.96 Mn |
| Mar 31, 2026 | 13.20 Mn |
| Dec 31, 2025 | 18.88 Mn |
| Sep 30, 2025 | 21.42 Mn |
| Jun 30, 2025 | 8.70 Mn |
| Mar 31, 2025 | 8.90 Mn |
| Dec 31, 2024 | 8.71 Mn |
| Sep 30, 2024 | 10.75 Mn |
| Jun 30, 2024 | 8.81 Mn |
| Mar 31, 2024 | 9.48 Mn |
| Dec 31, 2023 | 9.61 Mn |
| Sep 30, 2023 | 8.68 Mn |
| Jun 30, 2023 | 8.85 Mn |
| Mar 31, 2023 | 9.98 Mn |
| Dec 31, 2022 | 10.09 Mn |
| Sep 30, 2022 | 10.93 Mn |
| Jun 30, 2022 | 11.12 Mn |
| Mar 31, 2022 | 11.17 Mn |
| Dec 31, 2021 | 15.47 Mn |
| Sep 30, 2021 | 16.00 Mn |
API Access
Copper Property CTL Pass Through Trust 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=CPPTL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CPPTL", "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=CPPTL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();