Teradyne (TER) Change in Accrued Expenses (2009 - 2026)
Teradyne (TER) reported Change in Accrued Expenses of $225.81 million for Q3 2026, up 116.5% from $104.31 million a year earlier and up 65.0% from the prior quarter.
Teradyne (TER) Change in Accrued Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 27, 2026, Teradyne's Change in Accrued Expenses came in at $435.02 million, up 232.8% year-over-year; for FY2025, it was $208.85 million.
- Change in Accrued Expenses has a five-year compound annual growth rate of 23.3% (FY2020 to FY2025).
- By year, Change in Accrued Expenses came in at -$54.39 million in FY2024, $46.78 million in FY2023, -$60.51 million in FY2022 and $129.5 million in FY2021 (+77.0%).
- The Q3 2026 figure ranks as the highest quarterly Change in Accrued Expenses in data going back to Q3 2009.
- Year over year, Change in Accrued Expenses gained in three of the last five quarters, with growth averaging 247.3%.
- The high point for year-over-year Change in Accrued Expenses in five years was Q4 2025 (growth of 841.8%); the low point was Q4 2022 (a decline of 82.7%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $136.83 million (Q2 2026), -$15.03 million (Q1 2026) and $87.4 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 5,020.54 Bn | 4,766.00 Bn | 54.82 Bn | - |
| 2 | Cisco Systems | 371.11 Bn | 307.04 Bn | 11.06 Bn | 789.00 Mn |
| 3 | Arista Networks | 215.34 Bn | 164.54 Bn | 2.33 Bn | - |
| 4 | Dell Technologies | 212.13 Bn | 167.88 Bn | 9.83 Bn | - |
| 5 | Sony | 161.14 Bn | 95.68 Bn | 7.96 Bn | - |
| 6 | Sandisk | 122.92 Bn | 107.75 Bn | 9.38 Bn | -215.00 Mn |
| 7 | Seagate Technology Holdings | 105.29 Bn | 100.14 Bn | 2.43 Bn | 272.00 Mn |
| 8 | Western Digital | 96.46 Bn | 86.29 Bn | 2.53 Bn | -83.00 Mn |
| 9 | Hewlett Packard Enterprise | 59.75 Bn | 37.63 Bn | 4.93 Bn | - |
| 10 | Teradyne | 34.04 Bn | 32.65 Bn | 771.28 Mn | 225.81 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 27, 2026 | 225.81 Mn |
| Jun 28, 2026 | 136.83 Mn |
| Mar 29, 2026 | -15.03 Mn |
| Dec 31, 2025 | 87.40 Mn |
| Sep 28, 2025 | 104.31 Mn |
| Jun 29, 2025 | 27.09 Mn |
| Mar 30, 2025 | -9.95 Mn |
| Dec 31, 2024 | 9.28 Mn |
| Sep 29, 2024 | -10.66 Mn |
| Jun 30, 2024 | 52.54 Mn |
| Mar 31, 2024 | -105.55 Mn |
| Dec 31, 2023 | 42.78 Mn |
| Oct 1, 2023 | 28.51 Mn |
| Jul 2, 2023 | 58.69 Mn |
| Apr 2, 2023 | -83.21 Mn |
| Dec 31, 2022 | 11.18 Mn |
| Oct 2, 2022 | -28.07 Mn |
| Jul 3, 2022 | 80.77 Mn |
| Apr 3, 2022 | -124.38 Mn |
| Dec 31, 2021 | 64.44 Mn |
Teradyne 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=TER&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "TER", "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=TER&period=max&api_key=YOUR_API_KEY");
const data = await res.json();