V2X (VVX) EBITDA (2013 - 2026)
V2X (VVX) posted EBITDA of $82.1 million for Q2 2026, up 1.8% from $80.66 million a year earlier and up 13.7% from the prior quarter.
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Analysis
V2X (VVX) EBITDA (2013 - 2026) Analysis & Trends
For the trailing twelve months through Jul 3, 2026, EBITDA at V2X was $318.1 million, up 5.7% year-over-year; for FY2025, it came in at $306.79 million, up 11.9% from FY2024.
- Annual EBITDA has increased for five consecutive years, with a five-year compound annual growth rate of 42.8% (FY2020 to FY2025).
- In prior years, V2X's EBITDA was $274.09 million in FY2024 (+15.3%), $237.73 million in FY2023 (+100.8%), $118.4 million in FY2022 (+50.7%) and $78.57 million in FY2021 (+52.3%).
- Quarterly EBITDA has run from a low of $9.13 million in Q1 2022 to a high of $83.79 million in Q3 2025 over five years.
- On a year-over-year basis, EBITDA has increased in each of the last eight quarters, with growth averaging 18.8% over the last eight quarters.
- The strongest year-over-year quarter for EBITDA in the past five years was Q1 2023, with growth of 541.9%; the weakest was Q1 2022, with a decline of 55.6%.
- According to Business Quant data, EBITDA for the three prior quarters was $72.2 million (Q1 2026), $80.02 million (Q4 2025) and $83.79 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | -5.87 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 3.89 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 752.00 Mn |
| 4 | Lockheed Martin | 117.51 Bn | 104.24 Bn | 2.45 Bn | 2.88 Bn |
| 5 | Howmet Aerospace | 90.46 Bn | 86.07 Bn | 951.00 Mn | 795.00 Mn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 1.68 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 957.00 Mn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn | 1.46 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn | 2.10 Bn |
| 10 | V2X | 2.22 Bn | 1.24 Bn | 109.50 Mn | 82.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 3, 2026 | 82.10 Mn |
| Apr 3, 2026 | 72.20 Mn |
| Dec 31, 2025 | 80.02 Mn |
| Sep 26, 2025 | 83.79 Mn |
| Jun 27, 2025 | 80.66 Mn |
| Mar 28, 2025 | 62.34 Mn |
| Dec 31, 2024 | 79.68 Mn |
| Sep 27, 2024 | 78.37 Mn |
| Jun 28, 2024 | 56.85 Mn |
| Mar 29, 2024 | 59.18 Mn |
| Dec 31, 2023 | 67.28 Mn |
| Sep 29, 2023 | 48.92 Mn |
| Jun 30, 2023 | 62.79 Mn |
| Mar 31, 2023 | 58.60 Mn |
| Dec 31, 2022 | 55.88 Mn |
| Sep 30, 2022 | 34.11 Mn |
| Jul 1, 2022 | 18.77 Mn |
| Apr 1, 2022 | 9.13 Mn |
| Dec 31, 2021 | 14.26 Mn |
| Oct 1, 2021 | 17.18 Mn |
API Access
V2X EBITDA 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=ebitda&ticker=VVX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=VVX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();