Synopsys (SNPS) Change in Accured Expenses (2009 - 2026)
Synopsys' Change in Accured Expenses came in at -$37.29 million for fiscal Q1 2026 (quarter ended Jan 31, 2026), compared with -$313.65 million a year earlier.
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Analysis
Synopsys (SNPS) Change in Accured Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jan 31, 2026, Synopsys reported Change in Accured Expenses of $262.88 million, up 86.9% year-over-year; for FY2025 (ended Oct 31, 2025), it came in at -$13.49 million.
- Going back by fiscal year, Change in Accured Expenses was $187.56 million in FY2024 (+10.0%), $170.5 million in FY2023, -$34.07 million in FY2022 and $125.13 million in FY2021 (+10.0%).
- The five-year range for quarterly Change in Accured Expenses is -$313.65 million (fiscal Q1 2025) to $273.91 million (fiscal Q3 2025).
- Year-over-year, Change in Accured Expenses increased in two of the last four quarters, with growth averaging 10.9%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in fiscal Q4 2023 (growth of 892.0%), and the weakest in fiscal Q4 2022 (a decline of 83.2%).
- Business Quant data shows SNPS's Change in Accured Expenses at -$44.87 million (Q4 2025), $273.91 million (Q3 2025) and $71.12 million (Q2 2025) in the three fiscal quarters before Q1 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,563.73 Bn | 5,337.89 Bn | 72.14 Bn | 252.00 Mn |
| 2 | Taiwan Semiconductor Manufacturing | 2,381.64 Bn | 2,007.35 Bn | 27.22 Bn | - |
| 3 | Broadcom | 1,640.54 Bn | 1,566.58 Bn | 20.46 Bn | 372.00 Mn |
| 4 | Micron Technology | 1,238.95 Bn | 1,177.72 Bn | 35.06 Bn | 2.40 Bn |
| 5 | Advanced Micro Devices | 1,004.87 Bn | 961.62 Bn | 6.20 Bn | -652.00 Mn |
| 6 | Asml Holding | 697.02 Bn | 652.86 Bn | 5.90 Bn | - |
| 7 | Intel | 605.16 Bn | 489.89 Bn | 6.51 Bn | 803.00 Mn |
| 8 | Lam Research | 425.56 Bn | 402.36 Bn | 3.48 Bn | - |
| 9 | Applied Materials | 420.05 Bn | 385.49 Bn | 4.59 Bn | 633.00 Mn |
| 10 | Synopsys | 93.99 Bn | 90.38 Bn | 1.80 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jan 31, 2026 | -37.29 Mn |
| Oct 31, 2025 | -44.87 Mn |
| Jul 31, 2025 | 273.91 Mn |
| Apr 30, 2025 | 71.12 Mn |
| Jan 31, 2025 | -313.65 Mn |
| Oct 31, 2024 | 170.03 Mn |
| Jul 31, 2024 | 159.62 Mn |
| Apr 30, 2024 | 124.62 Mn |
| Jan 31, 2024 | -266.70 Mn |
| Oct 31, 2023 | 121.92 Mn |
| Jul 31, 2023 | 211.41 Mn |
| Apr 30, 2023 | -18.58 Mn |
| Jan 31, 2023 | -144.26 Mn |
| Oct 31, 2022 | 12.29 Mn |
| Jul 31, 2022 | 134.65 Mn |
| Apr 30, 2022 | 42.22 Mn |
| Jan 31, 2022 | -223.22 Mn |
| Oct 31, 2021 | 73.14 Mn |
| Jul 31, 2021 | 148.79 Mn |
| Apr 30, 2021 | 74.34 Mn |
API Access
Synopsys Change in Accured 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=SNPS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "SNPS", "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=SNPS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();