Pricesmart (PSMT) Total Liabilities (2010 - 2026)
Pricesmart (PSMT) posted Total Liabilities of $1.13 billion for fiscal Q3 2026 (quarter ended May 31, 2026), up 21.1% from $930.25 million a year earlier and up 2.1% from the prior quarter.
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Analysis
Pricesmart (PSMT) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Pricesmart's Total Liabilities came in at $1.02 billion, up 13.6% from FY2024.
- Annual Total Liabilities has increased for four consecutive fiscal years, with a five-year compound annual growth rate of 4.4% (FY2020 to FY2025).
- In prior fiscal years, Pricesmart's Total Liabilities was $899.73 million in FY2024 (+0.1%), $898.57 million in FY2023 (+9.9%), $817.33 million in FY2022 (+3.5%) and $789.58 million in FY2021 (-4.2%).
- The fiscal Q3 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 five quarters, with growth averaging 8.5% 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 Q4 2021, with a decline of 4.2%.
- According to Business Quant data, Total Liabilities for the three prior fiscal quarters was $1.1 billion (Q2 2026), $1.09 billion (Q1 2026) and $1.02 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 940.16 Bn | 896.60 Bn | 49.13 Bn | 189.41 Bn |
| 2 | Costco Wholesale | 441.91 Bn | 365.19 Bn | 12.19 Bn | 53.24 Bn |
| 3 | Sysco | 39.57 Bn | 33.82 Bn | 4.13 Bn | 25.73 Bn |
| 4 | Kroger | 38.12 Bn | 24.27 Bn | 7.86 Bn | 43.65 Bn |
| 5 | Dollar General | 29.62 Bn | 24.30 Bn | 3.68 Bn | 22.88 Bn |
| 6 | Caseys General Stores | 25.43 Bn | 23.42 Bn | 1.24 Bn | 5.03 Bn |
| 7 | Dollar Tree | 23.72 Bn | 20.34 Bn | 2.10 Bn | 10.60 Bn |
| 8 | US Foods Holding | 22.36 Bn | 22.15 Bn | 1.92 Bn | 10.06 Bn |
| 9 | Tractor Supply | 17.18 Bn | 16.35 Bn | 1.68 Bn | 9.53 Bn |
| 10 | Pricesmart | 5.28 Bn | 4.01 Bn | 262.22 Mn | 1.13 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| 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 |
| Aug 31, 2021 | 789.58 Mn |
API Access
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_KEYimport 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();