Postal Realty Trust (PSTL) Total Liabilities (2018 - 2026)
Postal Realty Trust (PSTL) reported Total Liabilities of $419.29 million for Q2 2026, up 14.8% from $365.27 million a year earlier but down 0.7% from the prior quarter.
Postal Realty Trust (PSTL) Total Liabilities (2018 - 2026) Analysis & Trends
At the end of FY2025, Postal Realty Trust posted Total Liabilities of $399.5 million, up 21.3% from FY2024.
- Total Liabilities has increased for four consecutive years, with a five-year compound annual growth rate of 23.5% (FY2020 to FY2025).
- By year, Total Liabilities came in at $329.32 million in FY2024 (+23.9%), $265.72 million in FY2023 (+22.1%), $217.59 million in FY2022 (+93.9%) and $112.24 million in FY2021 (-19.4%).
- Five-year quarterly Total Liabilities spans a low of $112.24 million in Q4 2021 and a high of $422.09 million in Q1 2026.
- Year over year, Total Liabilities has now increased in each of the last 18 quarters, with growth averaging 22.3% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q4 2022 (growth of 93.9%); the low point was Q4 2021 (a decline of 19.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $422.09 million (Q1 2026), $399.5 million (Q4 2025) and $386.71 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Welltower | 166.01 Bn | 148.52 Bn | 1.39 Bn | 22.44 Bn |
| 2 | Prologis | 121.16 Bn | 125.55 Bn | - | 42.89 Bn |
| 3 | Simon Property | 65.49 Bn | 66.75 Bn | - | 34.13 Bn |
| 4 | Realty Income | 51.38 Bn | 53.76 Bn | - | 34.51 Bn |
| 5 | Public Storage | 49.67 Bn | 48.75 Bn | - | 10.83 Bn |
| 6 | Ventas | 43.61 Bn | 42.81 Bn | - | 14.95 Bn |
| 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 | 18.67 Bn |
| 9 | Vivmark Residential | 22.78 Bn | 22.97 Bn | - | 9.58 Bn |
| 10 | Postal Realty Trust | 692.40 Mn | 775.07 Mn | - | 419.29 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 419.29 Mn |
| Mar 31, 2026 | 422.09 Mn |
| Dec 31, 2025 | 399.50 Mn |
| Sep 30, 2025 | 386.71 Mn |
| Jun 30, 2025 | 365.27 Mn |
| Mar 31, 2025 | 339.11 Mn |
| Dec 31, 2024 | 329.32 Mn |
| Sep 30, 2024 | 306.09 Mn |
| Jun 30, 2024 | 298.63 Mn |
| Mar 31, 2024 | 270.80 Mn |
| Dec 31, 2023 | 265.72 Mn |
| Sep 30, 2023 | 254.37 Mn |
| Jun 30, 2023 | 245.58 Mn |
| Mar 31, 2023 | 233.10 Mn |
| Dec 31, 2022 | 217.59 Mn |
| Sep 30, 2022 | 208.24 Mn |
| Jun 30, 2022 | 194.43 Mn |
| Mar 31, 2022 | 138.84 Mn |
| Dec 31, 2021 | 112.24 Mn |
| Sep 30, 2021 | 143.15 Mn |
Postal Realty Trust Total Liabilities 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-liabilities&ticker=PSTL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=PSTL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();