Vertiv Holdings (VRT) Change in Accrued Expenses (2018 - 2026)
Vertiv Holdings' Change in Accrued Expenses came in at $112.8 million for Q3 2026, up 80.5% from $62.5 million a year earlier but down 4.1% from the prior quarter.
Vertiv Holdings (VRT) Change in Accrued Expenses (2018 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2026, Vertiv Holdings reported Change in Accrued Expenses of $208.9 million; for FY2025, it came in at $93.1 million.
- Change in Accrued Expenses carries a five-year compound annual growth rate of 47.6% (FY2020 to FY2025).
- Going back by year, Change in Accrued Expenses was $7 million in FY2024 (-92.3%), $91.5 million in FY2023, -$22 million in FY2022 and -$43.4 million in FY2021.
- The five-year range for quarterly Change in Accrued Expenses is -$95.4 million (Q1 2026) to $117.6 million (Q2 2026).
- Year-over-year, Change in Accrued Expenses increased in three of the last four quarters, with growth averaging 102.2%.
- The fastest year-over-year change in Change in Accrued Expenses over five years came in Q3 2023 (growth of 592.3%), and the weakest in Q3 2022 (a decline of 88.0%).
- Business Quant data shows VRT's Change in Accrued Expenses at $117.6 million (Q2 2026), -$95.4 million (Q1 2026) and $73.9 million (Q4 2025) in the three quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 256.79 Bn | 228.09 Bn | 7.35 Bn | 762.00 Mn |
| 2 | Amphenol | 183.76 Bn | 178.46 Bn | 4.02 Bn | - |
| 3 | Deere | 181.25 Bn | 149.34 Bn | 4.66 Bn | 67.00 Mn |
| 4 | Eaton | 132.82 Bn | 129.76 Bn | 3.11 Bn | - |
| 5 | Parker-Hannifin | 115.39 Bn | 113.27 Bn | 2.26 Bn | - |
| 6 | 3M | 96.09 Bn | 77.53 Bn | 2.78 Bn | - |
| 7 | Emerson Electric | 90.66 Bn | 83.40 Bn | 2.66 Bn | 191.00 Mn |
| 8 | Illinois Tool Works | 79.95 Bn | 76.63 Bn | 1.91 Bn | 35.00 Mn |
| 9 | Vertiv Holdings | 70.25 Bn | 59.10 Bn | 1.64 Bn | 112.80 Mn |
| 10 | Tenaris | 62.09 Bn | 33.35 Bn | 1.07 Bn | - |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 112.80 Mn |
| Jun 30, 2026 | 117.60 Mn |
| Mar 31, 2026 | -95.40 Mn |
| Dec 31, 2025 | 73.90 Mn |
| Sep 30, 2025 | 62.50 Mn |
| Jun 30, 2025 | 36.30 Mn |
| Mar 31, 2025 | -79.60 Mn |
| Dec 31, 2024 | -10.20 Mn |
| Sep 30, 2024 | 25.60 Mn |
| Jun 30, 2024 | 60.10 Mn |
| Mar 31, 2024 | -68.50 Mn |
| Dec 31, 2023 | 46.00 Mn |
| Sep 30, 2023 | 18.00 Mn |
| Jun 30, 2023 | 44.00 Mn |
| Mar 31, 2023 | -16.50 Mn |
| Dec 31, 2022 | 29.50 Mn |
| Sep 30, 2022 | 2.60 Mn |
| Jun 30, 2022 | -21.50 Mn |
| Mar 31, 2022 | -32.60 Mn |
| Dec 31, 2021 | -49.10 Mn |
Vertiv Holdings 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=VRT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "VRT", "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=VRT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();