Buckle (BKE) Operating Expenses (2009 - 2026)
Buckle (BKE) posted Operating Expenses of $97.22 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 9.6% from $88.67 million a year earlier and up 31.3% from the prior quarter.
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Analysis
Buckle (BKE) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Aug 1, 2026, Operating Expenses at Buckle was $373.56 million, up 3.5% year-over-year; for FY2026 (ended Jan 31, 2026), it was $374.41 million, up 6.5% from FY2025.
- Annual Operating Expenses shows a five-year compound annual growth rate of 10.0% (FY2021 to FY2026).
- In prior fiscal years, Buckle's Operating Expenses was $351.42 million in FY2025 (+1.0%), $348.01 million in FY2024 (unchanged), $347.87 million in FY2023 (+9.6%) and $317.51 million in FY2022 (+36.5%).
- Quarterly Operating Expenses has run from a low of $74.02 million in fiscal Q1 2027 to a high of $109.32 million in fiscal Q4 2026 over five years.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 3.4%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q3 2022, with growth of 25.5%; the weakest was fiscal Q1 2027, with a decline of 11.3%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $74.02 million (Q1 2027), $109.32 million (Q4 2026) and $92.99 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Buckle | 2.22 Bn | 1.03 Bn | 153.02 Mn | 97.22 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 97.22 Mn |
| May 2, 2026 | 74.02 Mn |
| Jan 31, 2026 | 109.32 Mn |
| Nov 1, 2025 | 92.99 Mn |
| Aug 2, 2025 | 88.67 Mn |
| May 3, 2025 | 83.43 Mn |
| Feb 1, 2025 | 103.26 Mn |
| Nov 2, 2024 | 85.59 Mn |
| Aug 3, 2024 | 84.27 Mn |
| May 4, 2024 | 78.30 Mn |
| Feb 3, 2024 | 103.68 Mn |
| Oct 28, 2023 | 83.15 Mn |
| Jul 29, 2023 | 81.65 Mn |
| Apr 29, 2023 | 79.53 Mn |
| Jan 28, 2023 | 103.14 Mn |
| Oct 29, 2022 | 85.98 Mn |
| Jul 30, 2022 | 79.66 Mn |
| Apr 30, 2022 | 79.10 Mn |
| Jan 29, 2022 | 92.77 Mn |
| Oct 30, 2021 | 78.85 Mn |
API Access
Buckle 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=BKE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BKE", "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=BKE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();