Caseys General Stores (CASY) Accumulated Expenses (2010 - 2026)
Caseys General Stores (CASY) reported Accumulated Expenses of $377.01 million for fiscal Q1 2027 (quarter ended Jul 31, 2026), up 4.4% from $361.27 million a year earlier but down 11.4% from the prior quarter.
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Analysis
Caseys General Stores (CASY) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2026 (ended Apr 30, 2026), Caseys General Stores posted Accumulated Expenses of $425.45 million, up 929.4% from FY2025.
- Accumulated Expenses has a five-year compound annual growth rate of 77.3% (FY2021 to FY2026).
- By fiscal year, Accumulated Expenses came in at $41.33 million in FY2025 (+51.3%), $27.32 million in FY2024 (-5.3%), $28.86 million in FY2023 (+11.9%) and $25.8 million in FY2022 (+6.2%).
- Five-year quarterly Accumulated Expenses spans a low of $25.8 million in fiscal Q4 2022 and a high of $425.45 million in fiscal Q4 2026.
- Year over year, Accumulated Expenses has now increased in each of the last eight quarters, with growth averaging 132.6% over the last eight quarters.
- The high point for year-over-year Accumulated Expenses in five years was fiscal Q4 2026 (growth of 929.4%); the low point was fiscal Q4 2024 (a decline of 5.3%).
- Per Business Quant data, the three fiscal quarters before Q1 2027 came in at $425.45 million (Q4 2026), $396.89 million (Q3 2026) and $367.71 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Walmart | 824.47 Bn | 787.18 Bn | 49.13 Bn |
| 2 | Costco Wholesale | 403.75 Bn | 333.05 Bn | 9.01 Bn |
| 3 | Sysco | 37.36 Bn | 31.61 Bn | 4.13 Bn |
| 4 | Kroger | 34.63 Bn | 20.79 Bn | 7.86 Bn |
| 5 | Dollar General | 26.38 Bn | 21.06 Bn | 3.68 Bn |
| 6 | Caseys General Stores | 22.49 Bn | 20.48 Bn | 1.24 Bn |
| 7 | Dollar Tree | 21.40 Bn | 18.02 Bn | 2.10 Bn |
| 8 | US Foods Holding | 19.94 Bn | 19.74 Bn | 1.92 Bn |
| 9 | Tractor Supply | 16.33 Bn | 15.49 Bn | 1.68 Bn |
| 10 | Performance Food | 14.29 Bn | 14.07 Bn | 2.17 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 377.01 Mn |
| Apr 30, 2026 | 425.45 Mn |
| Jan 31, 2026 | 396.89 Mn |
| Oct 31, 2025 | 367.71 Mn |
| Jul 31, 2025 | 361.27 Mn |
| Apr 30, 2025 | 41.33 Mn |
| Jan 31, 2025 | 366.02 Mn |
| Oct 31, 2024 | 296.37 Mn |
| Jul 31, 2024 | 294.23 Mn |
| Apr 30, 2024 | 27.32 Mn |
| Jan 31, 2024 | 305.71 Mn |
| Oct 31, 2023 | 295.35 Mn |
| Jul 31, 2023 | 294.87 Mn |
| Apr 30, 2023 | 28.86 Mn |
| Jan 31, 2023 | 313.83 Mn |
| Oct 31, 2022 | 298.96 Mn |
| Jul 31, 2022 | 284.89 Mn |
| Apr 30, 2022 | 25.80 Mn |
| Jan 31, 2022 | 293.02 Mn |
| Oct 31, 2021 | 260.06 Mn |
API Access
Caseys General Stores Accumulated 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=accumulated-expenses&ticker=CASY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "CASY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=CASY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();