Pricesmart (PSMT) Total Liabilities (2010 - 2026)
Pricesmart (PSMT) posted Total Liabilities of $1.15 billion for fiscal Q4 2026 (quarter ended Aug 31, 2026), up 12.3% from $1.02 billion a year earlier and up 1.8% from the prior quarter.
Pricesmart (PSMT) Total Liabilities (2010 - 2026) Analysis & Trends
Since fiscal Q4 2010, Pricesmart has reported Total Liabilities for 63 quarters.
- Annual Total Liabilities has increased for five consecutive fiscal years, with a five-year compound annual growth rate of 7.8% (FY2021 to FY2026).
- In prior fiscal years, Pricesmart's Total Liabilities was $1.02 billion in FY2025 (+13.6%), $899.73 million in FY2024 (+0.1%), $898.57 million in FY2023 (+9.9%) and $817.33 million in FY2022 (+3.5%).
- The fiscal Q4 2026 figure stands as the highest quarterly Total Liabilities in data going back to fiscal Q4 2010.
- On a year-over-year basis, Total Liabilities has increased in each of the last six quarters, with growth averaging 10.1% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was fiscal Q3 2026, with growth of 21.1%; the weakest was fiscal Q2 2025, with a decline of 2.4%.
- According to Business Quant data, Total Liabilities for the three prior fiscal quarters was $1.13 billion (Q3 2026), $1.1 billion (Q2 2026) and $1.09 billion (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 996.32 Bn | 952.75 Bn | 49.13 Bn | 189.41 Bn |
| 2 | Costco Wholesale | 469.92 Bn | 393.20 Bn | 12.19 Bn | 53.24 Bn |
| 3 | Kroger | 40.99 Bn | 27.14 Bn | 7.86 Bn | 43.65 Bn |
| 4 | Sysco | 37.79 Bn | 29.71 Bn | 4.05 Bn | 26.41 Bn |
| 5 | Dollar General | 30.20 Bn | 24.88 Bn | 3.68 Bn | 22.88 Bn |
| 6 | Dollar Tree | 26.17 Bn | 22.79 Bn | 2.10 Bn | 10.60 Bn |
| 7 | Caseys General Stores | 25.41 Bn | 23.40 Bn | 1.24 Bn | 5.03 Bn |
| 8 | US Foods Holding | 23.76 Bn | 23.56 Bn | 1.90 Bn | 10.03 Bn |
| 9 | Tractor Supply | 19.62 Bn | 18.77 Bn | 1.42 Bn | 9.59 Bn |
| 10 | Pricesmart | 5.00 Bn | 3.72 Bn | 266.81 Mn | 1.15 Bn |
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 1.15 Bn |
| May 31, 2026 | 1.13 Bn |
| Feb 28, 2026 | 1.10 Bn |
| Nov 30, 2025 | 1.09 Bn |
| Aug 31, 2025 | 1.02 Bn |
| May 31, 2025 | 930.25 Mn |
| Feb 28, 2025 | 920.08 Mn |
| Nov 30, 2024 | 929.10 Mn |
| Aug 31, 2024 | 899.73 Mn |
| May 31, 2024 | 925.34 Mn |
| Feb 29, 2024 | 942.90 Mn |
| Nov 30, 2023 | 947.04 Mn |
| Aug 31, 2023 | 898.57 Mn |
| May 31, 2023 | 843.65 Mn |
| Feb 28, 2023 | 842.26 Mn |
| Nov 30, 2022 | 861.56 Mn |
| Aug 31, 2022 | 817.33 Mn |
| May 31, 2022 | 823.57 Mn |
| Feb 28, 2022 | 819.45 Mn |
| Nov 30, 2021 | 847.17 Mn |
Pricesmart 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=PSMT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PSMT", "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=PSMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();