Angiodynamics (ANGO) Change in Accrued Expenses (2009 - 2026)
Angiodynamics (ANGO) recorded Change in Accured Expenses of -$17.42 million in fiscal Q1 2027 (quarter ended Aug 31, 2026), compared with -$10.7 million a year earlier.
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Analysis
Angiodynamics (ANGO) Change in Accrued Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Angiodynamics' Change in Accured Expenses came in at -$12.56 million as of Aug 31, 2026; for FY2026 (ended May 31, 2026), it came in at -$5.83 million.
- Across earlier fiscal years, Change in Accured Expenses came in at -$15.88 million in FY2025, $27.53 million in FY2024, $2.14 million in FY2023 (-45.3%) and $3.91 million in FY2022 (-19.8%).
- The fiscal Q1 2027 figure is the lowest quarterly Change in Accured Expenses since fiscal Q1 2020.
- On a year-over-year basis, Change in Accured Expenses rose in 1 of the last four quarters, with growth averaging 2.9%.
- Peak year-over-year performance for Change in Accured Expenses in the last five years was growth of 235.7% in fiscal Q2 2023, against a decline of 76.0% in fiscal Q4 2025 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $7.7 million (Q4 2026), -$6.01 million (Q3 2026) and $3.18 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 266.22 Bn | 242.86 Bn | 5.13 Bn | - |
| 2 | Abbott Laboratories | 191.31 Bn | 165.77 Bn | 7.39 Bn | - |
| 3 | Danaher | 166.16 Bn | 145.82 Bn | 3.84 Bn | 30.00 Mn |
| 4 | Intuitive Surgical | 155.98 Bn | 136.40 Bn | 2.08 Bn | 80.10 Mn |
| 5 | Medtronic | 130.05 Bn | 96.18 Bn | 6.34 Bn | -531.00 Mn |
| 6 | Stryker | 123.40 Bn | 109.59 Bn | 4.25 Bn | 77.00 Mn |
| 7 | Boston Scientific | 64.81 Bn | 60.48 Bn | 3.43 Bn | 89.00 Mn |
| 8 | Edwards Lifesciences | 59.87 Bn | 43.18 Bn | 1.35 Bn | 67.20 Mn |
| 9 | Medline | 53.84 Bn | 50.96 Bn | 1.93 Bn | 255.00 Mn |
| 10 | Angiodynamics | 20.48 Mn | -146.80 Mn | 48.04 Mn | -17.42 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | -17.42 Mn |
| May 31, 2026 | 7.70 Mn |
| Feb 28, 2026 | -6.01 Mn |
| Nov 30, 2025 | 3.18 Mn |
| Aug 31, 2025 | -10.70 Mn |
| May 31, 2025 | 2.59 Mn |
| Feb 28, 2025 | -10.96 Mn |
| Nov 30, 2024 | 7.48 Mn |
| Aug 31, 2024 | -14.98 Mn |
| May 31, 2024 | 10.79 Mn |
| Feb 29, 2024 | 17.71 Mn |
| Nov 30, 2023 | 15.57 Mn |
| Aug 31, 2023 | -16.54 Mn |
| May 31, 2023 | 9.25 Mn |
| Feb 28, 2023 | -4.27 Mn |
| Nov 30, 2022 | 6.15 Mn |
| Aug 31, 2022 | -8.99 Mn |
| May 31, 2022 | 15.71 Mn |
| Feb 28, 2022 | -7.29 Mn |
| Nov 30, 2021 | 1.83 Mn |
API Access
Angiodynamics 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=ANGO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "ANGO", "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=ANGO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();