V2X (VVX) Accumulated Expenses (2013 - 2026)
V2X (VVX) posted Accumulated Expenses of $216.72 million for Q2 2026, down 24.4% from $286.82 million a year earlier and down 22.8% from the prior quarter.
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Analysis
V2X (VVX) Accumulated Expenses (2013 - 2026) Analysis & Trends
At the end of FY2025, V2X's Accumulated Expenses came in at $258.37 million, down 1.3% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 44.8% (FY2020 to FY2025).
- In prior years, V2X's Accumulated Expenses was $261.74 million in FY2024 (+22.5%), $213.7 million in FY2023 (+8.7%), $196.54 million in FY2022 (+257.1%) and $55.03 million in FY2021 (+35.4%).
- The Q2 2026 figure stands as the lowest quarterly Accumulated Expenses since Q4 2023.
- On a year-over-year basis, Accumulated Expenses has declined in each of the last three quarters, with growth averaging 3.4% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q2 2023, with growth of 428.6%; the weakest was Q2 2026, with a decline of 24.4%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $280.56 million (Q1 2026), $258.37 million (Q4 2025) and $255.3 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | General Electric | 294.76 Bn | 253.28 Bn | 5.02 Bn |
| 2 | Rtx | 257.78 Bn | 226.05 Bn | 5.81 Bn |
| 3 | Boeing | 146.35 Bn | 53.04 Bn | 2.41 Bn |
| 4 | Lockheed Martin | 137.41 Bn | 121.64 Bn | 2.44 Bn |
| 5 | General Dynamics | 93.80 Bn | 80.91 Bn | 2.18 Bn |
| 6 | Motorola Solutions | 79.05 Bn | 75.40 Bn | 1.68 Bn |
| 7 | Northrop Grumman | 77.53 Bn | 64.98 Bn | 2.35 Bn |
| 8 | Howmet Aerospace | 74.34 Bn | 69.94 Bn | 951.00 Mn |
| 9 | Honeywell International | 67.69 Bn | 19.81 Bn | 3.65 Bn |
| 10 | V2X | 2.28 Bn | 1.31 Bn | 109.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 3, 2026 | 216.72 Mn |
| Apr 3, 2026 | 280.56 Mn |
| Dec 31, 2025 | 258.37 Mn |
| Sep 26, 2025 | 255.30 Mn |
| Jun 27, 2025 | 286.82 Mn |
| Mar 28, 2025 | 282.09 Mn |
| Dec 31, 2024 | 261.74 Mn |
| Sep 27, 2024 | 235.38 Mn |
| Jun 28, 2024 | 242.40 Mn |
| Mar 29, 2024 | 267.43 Mn |
| Dec 31, 2023 | 213.70 Mn |
| Sep 29, 2023 | 237.89 Mn |
| Jun 30, 2023 | 255.41 Mn |
| Mar 31, 2023 | 198.10 Mn |
| Dec 31, 2022 | 196.54 Mn |
| Sep 30, 2022 | 172.03 Mn |
| Jul 1, 2022 | 48.32 Mn |
| Apr 1, 2022 | 55.42 Mn |
| Dec 31, 2021 | 55.03 Mn |
| Oct 1, 2021 | 46.80 Mn |
API Access
V2X Accumulated 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=accumulated-expenses&ticker=VVX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "VVX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=VVX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();