Postal Realty Trust (PSTL) Operating Expenses (2018 - 2026)
Postal Realty Trust's Operating Expenses came in at $17.33 million for Q2 2026, up 18.3% from $14.64 million a year earlier but down 0.5% from the prior quarter.
Postal Realty Trust (PSTL) Operating Expenses (2018 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Postal Realty Trust reported Operating Expenses of $65.71 million, up 9.8% year-over-year; for FY2025, it came in at $61.44 million, up 6.7% from FY2024.
- Operating Expenses has increased in each of the last seven years, with a five-year compound annual growth rate of 22.3% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $57.59 million in FY2024 (+15.8%), $49.72 million in FY2023 (+13.9%), $43.63 million in FY2022 (+28.3%) and $34.02 million in FY2021 (+51.8%).
- The five-year range for quarterly Operating Expenses is $8.95 million (Q3 2021) to $17.41 million (Q1 2026).
- Year-over-year, Operating Expenses has increased for 29 consecutive quarters, with growth averaging 11.0% over the last eight quarters.
- Across the past five years, year-over-year growth in Operating Expenses ran from 2.0% in Q3 2025 to 57.5% in Q3 2021.
- Business Quant data shows PSTL's Operating Expenses at $17.41 million (Q1 2026), $15.8 million (Q4 2025) and $15.18 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 166.01 Bn | 148.52 Bn | 1.39 Bn | 3.22 Bn |
| 2 | Prologis | 121.16 Bn | 125.55 Bn | - | 1.47 Bn |
| 3 | Simon Property | 65.49 Bn | 66.75 Bn | - | 900.79 Mn |
| 4 | Realty Income | 51.38 Bn | 53.76 Bn | - | 1.19 Bn |
| 5 | Public Storage | 49.67 Bn | 48.75 Bn | - | 766.20 Mn |
| 6 | Ventas | 43.61 Bn | 42.81 Bn | - | 1.68 Bn |
| 7 | Extra Space Storage | 27.79 Bn | 27.79 Bn | 642.43 Mn | 481.97 Mn |
| 8 | Vici Properties | 25.29 Bn | 23.41 Bn | 1.05 Bn | 315.61 Mn |
| 9 | Vivmark Residential | 22.78 Bn | 22.97 Bn | - | 566.18 Mn |
| 10 | Postal Realty Trust | 692.40 Mn | 775.07 Mn | - | 17.33 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 17.33 Mn |
| Mar 31, 2026 | 17.41 Mn |
| Dec 31, 2025 | 15.80 Mn |
| Sep 30, 2025 | 15.18 Mn |
| Jun 30, 2025 | 14.64 Mn |
| Mar 31, 2025 | 15.82 Mn |
| Dec 31, 2024 | 14.52 Mn |
| Sep 30, 2024 | 14.88 Mn |
| Jun 30, 2024 | 13.94 Mn |
| Mar 31, 2024 | 14.25 Mn |
| Dec 31, 2023 | 13.00 Mn |
| Sep 30, 2023 | 12.28 Mn |
| Jun 30, 2023 | 11.83 Mn |
| Mar 31, 2023 | 12.60 Mn |
| Dec 31, 2022 | 11.44 Mn |
| Sep 30, 2022 | 10.86 Mn |
| Jun 30, 2022 | 10.46 Mn |
| Mar 31, 2022 | 10.87 Mn |
| Dec 31, 2021 | 9.42 Mn |
| Sep 30, 2021 | 8.95 Mn |
Postal Realty 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=PSTL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PSTL", "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=PSTL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();