Monolithic Power Systems (MPWR) Accumulated Expenses (2014 - 2026)
Monolithic Power Systems (MPWR) recorded Accumulated Expenses of $222.08 million in Q2 2026, up 28.9% from $172.29 million a year earlier and up 3.9% from the prior quarter.
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Analysis
Monolithic Power Systems (MPWR) Accumulated Expenses (2014 - 2026) Analysis & Trends
At the end of FY2025, Monolithic Power Systems reported Accumulated Expenses of $145.13 million, up 13.3% from FY2024.
- Annual Accumulated Expenses has increased for 11 straight years, with a five-year compound annual growth rate of 18.2% (FY2020 to FY2025).
- Across earlier years, Accumulated Expenses came in at $128.12 million in FY2024 (+10.7%), $115.79 million in FY2023 (+1.9%), $113.68 million in FY2022 (+39.9%) and $81.28 million in FY2021 (+29.1%).
- The Q2 2026 figure is the highest quarterly Accumulated Expenses in data going back to Q4 2014.
- On a year-over-year basis, Accumulated Expenses has increased for nine consecutive quarters, with growth averaging 24.2% over the last eight quarters.
- Peak year-over-year performance for Accumulated Expenses in the last five years was growth of 49.4% in Q1 2022, against a decline of 11.6% in Q1 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $213.69 million (Q1 2026), $145.13 million (Q4 2025) and $201.51 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nvidia | 5,638.19 Bn | 5,412.36 Bn | 72.14 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,452.80 Bn | 2,078.51 Bn | 27.22 Bn |
| 3 | Broadcom | 1,695.44 Bn | 1,621.48 Bn | 20.46 Bn |
| 4 | Micron Technology | 1,213.55 Bn | 1,152.31 Bn | 35.06 Bn |
| 5 | Advanced Micro Devices | 1,034.54 Bn | 991.29 Bn | 6.20 Bn |
| 6 | Asml Holding | 719.69 Bn | 675.53 Bn | 5.90 Bn |
| 7 | Intel | 601.78 Bn | 486.52 Bn | 6.51 Bn |
| 8 | Lam Research | 434.81 Bn | 411.60 Bn | 3.48 Bn |
| 9 | Applied Materials | 428.57 Bn | 394.02 Bn | 4.59 Bn |
| 10 | Monolithic Power Systems | 70.75 Bn | 65.44 Bn | 541.07 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 222.08 Mn |
| Mar 31, 2026 | 213.69 Mn |
| Dec 31, 2025 | 145.13 Mn |
| Sep 30, 2025 | 201.51 Mn |
| Jun 30, 2025 | 172.29 Mn |
| Mar 31, 2025 | 161.31 Mn |
| Dec 31, 2024 | 128.12 Mn |
| Sep 30, 2024 | 139.43 Mn |
| Jun 30, 2024 | 131.35 Mn |
| Mar 31, 2024 | 137.87 Mn |
| Dec 31, 2023 | 115.79 Mn |
| Sep 30, 2023 | 120.68 Mn |
| Jun 30, 2023 | 113.41 Mn |
| Mar 31, 2023 | 155.96 Mn |
| Dec 31, 2022 | 113.68 Mn |
| Sep 30, 2022 | 109.06 Mn |
| Jun 30, 2022 | 91.32 Mn |
| Mar 31, 2022 | 111.09 Mn |
| Dec 31, 2021 | 81.28 Mn |
| Sep 30, 2021 | 79.76 Mn |
API Access
Monolithic Power Systems 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=MPWR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MPWR", "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=MPWR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();