Arteris (AIP) Change in Accrued Expenses (2020 - 2026)
Arteris (AIP) recorded Change in Accured Expenses of $3.43 million in Q2 2026, up 101.5% from $1.7 million a year earlier.
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Analysis
Arteris (AIP) Change in Accrued Expenses (2020 - 2026) Analysis & Trends
On a TTM basis, Arteris' Change in Accured Expenses came in at $614,000 as of Jun 30, 2026, down 77.3% year-over-year; for FY2025, it came in at $3.25 million, up 5.7% from FY2024.
- Annual Change in Accured Expenses has increased for three straight years, with a five-year compound annual growth rate of 1.5% (FY2020 to FY2025).
- Across earlier years, Change in Accured Expenses came in at $3.08 million in FY2024 (+24.8%), $2.47 million in FY2023 (+377.2%), $517,000 in FY2022 (-81.8%) and $2.84 million in FY2021 (-6.0%).
- The Q2 2026 figure is the highest quarterly Change in Accured Expenses in data going back to Q4 2020.
- On a year-over-year basis, Change in Accured Expenses rose in four of the last five quarters, with growth averaging 40.8%.
- Peak year-over-year performance for Change in Accured Expenses in the last five years was growth of 110.2% in Q3 2023, against a decline of 67.2% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at -$6.34 million (Q1 2026), $1.59 million (Q4 2025) and $1.94 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | SK hynix | 24,576.54 Bn | 24,560.31 Bn | 43.99 Bn | - |
| 2 | Taiwan Semiconductor Manufacturing | 10,284.32 Bn | 9,899.31 Bn | 27.22 Bn | 157.82 Mn |
| 3 | Nvidia | 4,083.27 Bn | 3,857.43 Bn | 72.14 Bn | 252.00 Mn |
| 4 | Broadcom | 1,582.22 Bn | 1,508.26 Bn | 20.46 Bn | -619.00 Mn |
| 5 | Advanced Micro Devices | 844.94 Bn | 793.16 Bn | 7.21 Bn | 323.00 Mn |
| 6 | Micron Technology | 820.10 Bn | 725.74 Bn | 47.05 Bn | 5.38 Bn |
| 7 | Asml Holding | 581.15 Bn | 536.84 Bn | 5.90 Bn | - |
| 8 | Intel | 308.67 Bn | 171.38 Bn | 7.10 Bn | 165.00 Mn |
| 9 | Applied Materials | 295.64 Bn | 261.08 Bn | 4.59 Bn | 633.00 Mn |
| 10 | Arteris | 947.96 Mn | 629.01 Mn | 22.32 Mn | 1.19 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 1.19 Mn |
| Jun 30, 2026 | 3.43 Mn |
| Mar 31, 2026 | -6.34 Mn |
| Dec 31, 2025 | 1.59 Mn |
| Sep 30, 2025 | 1.94 Mn |
| Jun 30, 2025 | 1.70 Mn |
| Mar 31, 2025 | -1.98 Mn |
| Dec 31, 2024 | 1.59 Mn |
| Sep 30, 2024 | 1.39 Mn |
| Jun 30, 2024 | -801,000.00 |
| Mar 31, 2024 | 904,000.00 |
| Dec 31, 2023 | 923,000.00 |
| Sep 30, 2023 | 1.53 Mn |
| Jun 30, 2023 | 990,000.00 |
| Mar 31, 2023 | -974,000.00 |
| Dec 31, 2022 | 494,000.00 |
| Sep 30, 2022 | 727,000.00 |
| Jun 30, 2022 | 666,000.00 |
| Mar 31, 2022 | -1.37 Mn |
| Dec 31, 2021 | 1.51 Mn |
API Access
Arteris Change in Accrued 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=change-in-accured-expenses&ticker=AIP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "AIP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=AIP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();