Alpha & Omega Semiconductor (AOSL) Accumulated Expenses (2010 - 2026)
Alpha & Omega Semiconductor (AOSL) reported Accumulated Expenses of $60.09 million for fiscal Q1 2027 (quarter ended Sep 30, 2026), down 11.9% from $68.18 million a year earlier but up 4.2% from the prior quarter.
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Analysis
Alpha & Omega Semiconductor (AOSL) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2026 (ended Jun 30, 2026), Alpha & Omega Semiconductor posted Accumulated Expenses of $57.68 million, down 2.3% from FY2025.
- Accumulated Expenses has declined for four consecutive fiscal years, with a five-year compound annual growth rate of -3.7% (FY2021 to FY2026).
- By fiscal year, Accumulated Expenses came in at $59.03 million in FY2025 (-18.4%), $72.37 million in FY2024 (-9.0%), $79.53 million in FY2023 (-32.0%) and $116.89 million in FY2022 (+68.2%).
- Five-year quarterly Accumulated Expenses spans a low of $57.68 million in fiscal Q4 2026 and a high of $116.89 million in fiscal Q4 2022.
- Year over year, Accumulated Expenses has now declined in each of the last 15 quarters, with an average decline of 10.6% over the last eight quarters.
- The high point for year-over-year Accumulated Expenses in five years was fiscal Q4 2022 (growth of 68.2%); the low point was fiscal Q4 2023 (a decline of 32.0%).
- Per Business Quant data, the three fiscal quarters before Q1 2027 came in at $57.68 million (Q4 2026), $59.01 million (Q3 2026) and $57.83 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | SK hynix | 24,980.27 Bn | 24,964.04 Bn | 43.99 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 10,337.48 Bn | 9,919.73 Bn | 31.04 Bn |
| 3 | Nvidia | 3,939.34 Bn | 3,713.50 Bn | 72.14 Bn |
| 4 | Broadcom | 1,653.85 Bn | 1,579.89 Bn | 20.46 Bn |
| 5 | Micron Technology | 880.27 Bn | 785.91 Bn | 47.05 Bn |
| 6 | Advanced Micro Devices | 875.86 Bn | 824.07 Bn | 7.21 Bn |
| 7 | Asml Holding | 576.26 Bn | 531.95 Bn | 5.90 Bn |
| 8 | Intel | 316.79 Bn | 179.50 Bn | 7.10 Bn |
| 9 | Applied Materials | 294.03 Bn | 294.03 Bn | 5.25 Bn |
| 10 | Alpha & Omega Semiconductor | 824.30 Mn | 79.34 Mn | 43.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 60.09 Mn |
| Jun 30, 2026 | 57.68 Mn |
| Mar 31, 2026 | 59.01 Mn |
| Dec 31, 2025 | 57.83 Mn |
| Sep 30, 2025 | 68.18 Mn |
| Jun 30, 2025 | 59.03 Mn |
| Mar 31, 2025 | 64.39 Mn |
| Dec 31, 2024 | 71.39 Mn |
| Sep 30, 2024 | 71.44 Mn |
| Jun 30, 2024 | 72.37 Mn |
| Mar 31, 2024 | 73.59 Mn |
| Dec 31, 2023 | 77.68 Mn |
| Sep 30, 2023 | 83.95 Mn |
| Jun 30, 2023 | 79.53 Mn |
| Mar 31, 2023 | 90.03 Mn |
| Dec 31, 2022 | 98.11 Mn |
| Sep 30, 2022 | 108.35 Mn |
| Jun 30, 2022 | 116.89 Mn |
| Mar 31, 2022 | 91.33 Mn |
| Dec 31, 2021 | 95.21 Mn |
API Access
Alpha & Omega Semiconductor 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=AOSL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "AOSL", "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=AOSL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();