Sitime (SITM) Accumulated Expenses (2018 - 2026)
Sitime (SITM) posted Accumulated Expenses of $80.84 million for Q2 2026, down 14.4% from $94.48 million a year earlier but up 52.0% from the prior quarter.
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Analysis
Sitime (SITM) Accumulated Expenses (2018 - 2026) Analysis & Trends
At the end of FY2025, Sitime's Accumulated Expenses came in at $62.68 million, down 26.7% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 37.1% (FY2020 to FY2025).
- In prior years, Sitime's Accumulated Expenses was $85.56 million in FY2024 (-24.1%), $112.7 million in FY2023 (+495.9%), $18.91 million in FY2022 (-22.1%) and $24.28 million in FY2021 (+87.3%).
- Quarterly Accumulated Expenses has run from a low of $17.02 million in Q1 2023 to a high of $112.7 million in Q4 2023 over five years.
- On a year-over-year basis, Accumulated Expenses has declined in each of the last three quarters, with growth averaging 30.5% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q1 2024, with growth of 538.1%; the weakest was Q1 2026, with a decline of 35.1%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $53.17 million (Q1 2026), $62.68 million (Q4 2025) and $91.81 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 | Sitime | 18.81 Bn | 14.48 Bn | 99.14 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 80.84 Mn |
| Mar 31, 2026 | 53.17 Mn |
| Dec 31, 2025 | 62.68 Mn |
| Sep 30, 2025 | 91.81 Mn |
| Jun 30, 2025 | 94.48 Mn |
| Mar 31, 2025 | 81.89 Mn |
| Dec 31, 2024 | 85.56 Mn |
| Sep 30, 2024 | 76.98 Mn |
| Jun 30, 2024 | 65.87 Mn |
| Mar 31, 2024 | 108.61 Mn |
| Dec 31, 2023 | 112.70 Mn |
| Sep 30, 2023 | 18.96 Mn |
| Jun 30, 2023 | 20.70 Mn |
| Mar 31, 2023 | 17.02 Mn |
| Dec 31, 2022 | 18.91 Mn |
| Sep 30, 2022 | 18.45 Mn |
| Jun 30, 2022 | 22.00 Mn |
| Mar 31, 2022 | 21.57 Mn |
| Dec 31, 2021 | 24.28 Mn |
| Sep 30, 2021 | 20.46 Mn |
API Access
Sitime 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=SITM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "SITM", "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=SITM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();