Hour Loop (HOUR) Operating Expenses (2021 - 2026)
Hour Loop's Operating Expenses came in at $14.88 million for Q1 2026, up 12.5% from $13.22 million a year earlier but down 48.1% from the prior quarter.
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Analysis
Hour Loop (HOUR) Operating Expenses (2021 - 2026) Analysis & Trends
Over the trailing twelve months to Mar 31, 2026, Hour Loop reported Operating Expenses of $73.82 million, up 3.1% year-over-year; for FY2025, it came in at $72.17 million, up 1.3% from FY2024.
- Operating Expenses has increased in each of the last five years, with a five-year compound annual growth rate of 31.5% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $71.28 million in FY2024 (+2.5%), $69.52 million in FY2023 (+36.6%), $50.9 million in FY2022 (+73.5%) and $29.33 million in FY2021 (+60.0%).
- The five-year range for quarterly Operating Expenses is $5.32 million (Q3 2021) to $30.82 million (Q4 2023).
- Year-over-year, Operating Expenses has increased for three consecutive quarters, with growth averaging 3.8% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2022 (growth of 82.7%), and the weakest in Q4 2024 (a decline of 11.2%).
- Business Quant data shows HOUR's Operating Expenses at $28.64 million (Q4 2025), $16.43 million (Q3 2025) and $13.88 million (Q2 2025) in the three quarters before Q1 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,654.24 Bn | 2,170.93 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 289.19 Bn | 282.43 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 143.39 Bn | 120.94 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.29 Bn | 98.25 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.79 Bn | 58.72 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 72.00 Bn | 66.59 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.61 Bn | 69.69 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 66.52 Bn | 58.12 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 47.57 Bn | 46.47 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Hour Loop | 67.22 Mn | 67.22 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 14.88 Mn |
| Dec 31, 2025 | 28.64 Mn |
| Sep 30, 2025 | 16.43 Mn |
| Jun 30, 2025 | 13.88 Mn |
| Mar 31, 2025 | 13.22 Mn |
| Dec 31, 2024 | 27.36 Mn |
| Sep 30, 2024 | 16.32 Mn |
| Jun 30, 2024 | 14.69 Mn |
| Mar 31, 2024 | 12.91 Mn |
| Dec 31, 2023 | 30.82 Mn |
| Sep 30, 2023 | 15.26 Mn |
| Jun 30, 2023 | 12.20 Mn |
| Mar 31, 2023 | 11.23 Mn |
| Dec 31, 2022 | 25.43 Mn |
| Sep 30, 2022 | 9.52 Mn |
| Jun 30, 2022 | 8.76 Mn |
| Mar 31, 2022 | 7.20 Mn |
| Dec 31, 2021 | 13.92 Mn |
| Sep 30, 2021 | 5.32 Mn |
| Jun 30, 2021 | 5.73 Mn |
API Access
Hour Loop 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=HOUR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HOUR", "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=HOUR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();