V2X (VVX) Operating Expenses (2013 - 2026)
V2X (VVX) reported Operating Expenses of $55.69 million for Q2 2026, up 30.1% from $42.79 million a year earlier but down 9.8% from the prior quarter.
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Analysis
V2X (VVX) Operating Expenses (2013 - 2026) Analysis & Trends
Over the twelve months ended Jul 3, 2026, V2X's Operating Expenses came in at $209.94 million, up 14.1% year-over-year; for FY2025, it was $179.11 million, down 2.5% from FY2024.
- Operating Expenses has declined for three consecutive years, though with a five-year compound annual growth rate of 17.3% (FY2020 to FY2025).
- By year, Operating Expenses came in at $183.76 million in FY2024 (-12.7%), $210.44 million in FY2023 (-12.0%), $239.24 million in FY2022 (+143.1%) and $98.4 million in FY2021 (+22.0%).
- Five-year quarterly Operating Expenses spans a low of $21.36 million in Q4 2021 and a high of $92.6 million in Q3 2022.
- Year over year, Operating Expenses gained in three of the last eight quarters, with growth averaging 5.0%.
- The high point for year-over-year Operating Expenses in five years was Q4 2022 (growth of 297.8%); the low point was Q3 2023 (a decline of 46.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $61.73 million (Q1 2026), $53.68 million (Q4 2025) and $38.84 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 117.51 Bn | 104.24 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 90.46 Bn | 86.07 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn | 1.87 Bn |
| 10 | V2X | 2.22 Bn | 1.24 Bn | 109.50 Mn | 55.69 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 3, 2026 | 55.69 Mn |
| Apr 3, 2026 | 61.73 Mn |
| Dec 31, 2025 | 53.68 Mn |
| Sep 26, 2025 | 38.84 Mn |
| Jun 27, 2025 | 42.79 Mn |
| Mar 28, 2025 | 43.81 Mn |
| Dec 31, 2024 | 55.86 Mn |
| Sep 27, 2024 | 41.55 Mn |
| Jun 28, 2024 | 46.41 Mn |
| Mar 29, 2024 | 39.94 Mn |
| Dec 31, 2023 | 59.42 Mn |
| Sep 29, 2023 | 49.64 Mn |
| Jun 30, 2023 | 53.13 Mn |
| Mar 31, 2023 | 48.25 Mn |
| Dec 31, 2022 | 84.95 Mn |
| Sep 30, 2022 | 92.60 Mn |
| Jul 1, 2022 | 29.74 Mn |
| Apr 1, 2022 | 31.96 Mn |
| Dec 31, 2021 | 21.36 Mn |
| Oct 1, 2021 | 27.62 Mn |
API Access
V2X Operating 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=operating-expenses&ticker=VVX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-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=operating-expenses&ticker=VVX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();