Shoe Station (SHOE) Operating Expenses (2011 - 2026)
Shoe Station (SHOE) reported Operating Expenses of $83 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), down 11.3% from $93.58 million a year earlier and down 13.7% from the prior quarter.
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Analysis
Shoe Station (SHOE) Operating Expenses (2011 - 2026) Analysis & Trends
Over the twelve months ended Aug 1, 2026, Shoe Station's Operating Expenses came in at $350.13 million, up 2.7% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $348.39 million, up 3.2% from FY2025.
- Operating Expenses has increased for six consecutive fiscal years, with a five-year compound annual growth rate of 6.2% (FY2021 to FY2026).
- By fiscal year, Operating Expenses came in at $337.64 million in FY2025 (+3.0%), $327.89 million in FY2024 (+1.9%), $321.72 million in FY2023 (+0.8%) and $319.13 million in FY2022 (+23.6%).
- Five-year quarterly Operating Expenses spans a low of $74.34 million in fiscal Q2 2023 and a high of $96.14 million in fiscal Q1 2027.
- Year over year, Operating Expenses gained in four of the last eight quarters, with growth averaging 1.1%.
- The high point for year-over-year Operating Expenses in five years was fiscal Q4 2022 (growth of 31.5%); the low point was fiscal Q2 2027 (a decline of 11.3%).
- Per Business Quant data, the three fiscal quarters before Q2 2027 came in at $96.14 million (Q1 2027), $77.79 million (Q4 2026) and $93.21 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 | Shoe Station | 355.29 Mn | -144.09 Mn | 90.61 Mn | 83.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 83.00 Mn |
| May 2, 2026 | 96.14 Mn |
| Jan 31, 2026 | 77.79 Mn |
| Nov 1, 2025 | 93.21 Mn |
| Aug 2, 2025 | 93.58 Mn |
| May 3, 2025 | 83.81 Mn |
| Feb 1, 2025 | 77.63 Mn |
| Nov 2, 2024 | 85.85 Mn |
| Aug 3, 2024 | 89.86 Mn |
| May 4, 2024 | 84.29 Mn |
| Feb 3, 2024 | 79.74 Mn |
| Oct 28, 2023 | 89.77 Mn |
| Jul 29, 2023 | 80.80 Mn |
| Apr 29, 2023 | 77.58 Mn |
| Jan 28, 2023 | 82.63 Mn |
| Oct 29, 2022 | 87.27 Mn |
| Jul 30, 2022 | 74.34 Mn |
| Apr 30, 2022 | 77.48 Mn |
| Jan 29, 2022 | 88.91 Mn |
| Oct 30, 2021 | 81.63 Mn |
API Access
Shoe Station 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=SHOE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SHOE", "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=SHOE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();