iPower (IPW) Operating Expenses (2020 - 2026)
iPower (IPW) reported Operating Expenses of $6.49 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), down 18.7% from $7.98 million a year earlier but up 241.6% from the prior quarter.
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Analysis
iPower (IPW) Operating Expenses (2020 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), iPower posted Operating Expenses of $18.47 million, down 45.2% from FY2025.
- Operating Expenses has declined for three consecutive fiscal years, with a five-year compound annual growth rate of -1.4% (FY2021 to FY2026).
- By fiscal year, Operating Expenses came in at $33.7 million in FY2025 (-13.8%), $39.08 million in FY2024 (-19.0%), $48.28 million in FY2023 (+56.3%) and $30.89 million in FY2022 (+55.5%).
- Five-year quarterly Operating Expenses spans a low of $1.9 million in fiscal Q3 2026 and a high of $14.58 million in fiscal Q1 2023.
- Year over year, Operating Expenses has now declined in each of the last four quarters, with an average decline of 26.0% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was fiscal Q1 2023 (growth of 142.0%); the low point was fiscal Q3 2026 (a decline of 73.6%).
- Per Business Quant data, the three fiscal quarters before Q4 2026 came in at $1.9 million (Q3 2026), $5.58 million (Q2 2026) and $6.5 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,829.77 Bn | 2,346.47 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 312.24 Bn | 305.48 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 162.20 Bn | 139.75 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 109.75 Bn | 102.72 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.33 Bn | 58.26 Bn | 2.12 Bn | 1.02 Bn |
| 6 | O Reilly Automotive | 73.38 Bn | 72.47 Bn | 2.52 Bn | 1.53 Bn |
| 7 | Target | 69.96 Bn | 64.55 Bn | 8.94 Bn | 5.73 Bn |
| 8 | Autozone | 51.69 Bn | 50.59 Bn | 2.52 Bn | 1.60 Bn |
| 9 | Carvana | 43.50 Bn | 33.99 Bn | 1.38 Bn | 704.00 Mn |
| 10 | iPower | 9,572.67 | -4.10 Mn | -2.80 Mn | 6.49 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.49 Mn |
| Mar 31, 2026 | 1.90 Mn |
| Dec 31, 2025 | 5.58 Mn |
| Sep 30, 2025 | 6.50 Mn |
| Jun 30, 2025 | 7.98 Mn |
| Mar 31, 2025 | 7.19 Mn |
| Dec 31, 2024 | 7.71 Mn |
| Sep 30, 2024 | 11.23 Mn |
| Jun 30, 2024 | 7.42 Mn |
| Mar 31, 2024 | 8.77 Mn |
| Dec 31, 2023 | 9.87 Mn |
| Sep 30, 2023 | 13.03 Mn |
| Jun 30, 2023 | 12.05 Mn |
| Mar 31, 2023 | 9.60 Mn |
| Dec 31, 2022 | 12.05 Mn |
| Sep 30, 2022 | 14.58 Mn |
| Jun 30, 2022 | 10.61 Mn |
| Mar 31, 2022 | 7.83 Mn |
| Dec 31, 2021 | 6.42 Mn |
| Sep 30, 2021 | 6.02 Mn |
API Access
iPower 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=IPW&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IPW", "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=IPW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();