Pricesmart (PSMT) Operating Expenses (2010 - 2026)
Pricesmart (PSMT) posted Operating Expenses of $1.42 billion for fiscal Q3 2026 (quarter ended May 31, 2026), up 12.3% from $1.26 billion a year earlier but down 0.3% from the prior quarter.
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Analysis
Pricesmart (PSMT) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through May 31, 2026, Operating Expenses at Pricesmart was $5.43 billion, up 10.1% year-over-year; for FY2025 (ended Aug 31, 2025), it was $5.04 billion, up 7.3% from FY2024.
- Annual Operating Expenses has increased for 15 consecutive fiscal years, with a five-year compound annual growth rate of 9.5% (FY2020 to FY2025).
- In prior fiscal years, Pricesmart's Operating Expenses was $4.69 billion in FY2024 (+11.0%), $4.23 billion in FY2023 (+8.4%), $3.9 billion in FY2022 (+12.6%) and $3.46 billion in FY2021 (+8.0%).
- Quarterly Operating Expenses has run from a low of $877.15 million in fiscal Q4 2021 to a high of $1.42 billion in fiscal Q2 2026 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last 61 quarters, with growth averaging 8.7% over the last eight quarters.
- Over the past five years, the year-over-year growth in Operating Expenses ranged from 5.7% (fiscal Q3 2023) to 16.0% (fiscal Q3 2022).
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $1.42 billion (Q2 2026), $1.32 billion (Q1 2026) and $1.28 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 847.32 Bn | 810.03 Bn | 49.13 Bn | 39.75 Bn |
| 2 | Costco Wholesale | 410.07 Bn | 339.37 Bn | 9.01 Bn | 6.19 Bn |
| 3 | Sysco | 37.60 Bn | 31.85 Bn | 4.13 Bn | 3.15 Bn |
| 4 | Kroger | 35.90 Bn | 22.05 Bn | 7.86 Bn | 198.00 Mn |
| 5 | Dollar General | 27.06 Bn | 21.73 Bn | 3.68 Bn | 2.91 Bn |
| 6 | Caseys General Stores | 22.17 Bn | 20.17 Bn | 1.24 Bn | 754.11 Mn |
| 7 | Dollar Tree | 21.26 Bn | 17.89 Bn | 2.10 Bn | 1.43 Bn |
| 8 | US Foods Holding | 20.27 Bn | 20.07 Bn | 1.92 Bn | 1.48 Bn |
| 9 | Tractor Supply | 16.44 Bn | 15.61 Bn | 1.68 Bn | 1.02 Bn |
| 10 | Pricesmart | 5.26 Bn | 4.00 Bn | 262.22 Mn | 1.42 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 1.42 Bn |
| Feb 28, 2026 | 1.42 Bn |
| Nov 30, 2025 | 1.32 Bn |
| Aug 31, 2025 | 1.28 Bn |
| May 31, 2025 | 1.26 Bn |
| Feb 28, 2025 | 1.30 Bn |
| Nov 30, 2024 | 1.20 Bn |
| Aug 31, 2024 | 1.18 Bn |
| May 31, 2024 | 1.18 Bn |
| Feb 29, 2024 | 1.23 Bn |
| Nov 30, 2023 | 1.11 Bn |
| Aug 31, 2023 | 1.09 Bn |
| May 31, 2023 | 1.05 Bn |
| Feb 28, 2023 | 1.09 Bn |
| Nov 30, 2022 | 999.28 Mn |
| Aug 31, 2022 | 982.41 Mn |
| May 31, 2022 | 997.05 Mn |
| Feb 28, 2022 | 990.24 Mn |
| Nov 30, 2021 | 929.34 Mn |
| Aug 31, 2021 | 877.15 Mn |
API Access
Pricesmart 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=PSMT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=PSMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();