Parsons (PSN) EBITDA (2018 - 2026)
Parsons (PSN) posted EBITDA of $37.93 million for Q2 2026, down 69.5% from $124.25 million a year earlier and down 71.2% from the prior quarter.
Parsons (PSN) EBITDA (2018 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EBITDA at Parsons was $443.2 million, down 15.7% year-over-year; for FY2025, it came in at $534.56 million, up 1.4% from FY2024.
- Annual EBITDA has increased for four consecutive years, with a five-year compound annual growth rate of 11.8% (FY2020 to FY2025).
- In prior years, Parsons' EBITDA was $527.32 million in FY2024 (+29.1%), $408.33 million in FY2023 (+33.4%), $306.17 million in FY2022 (+10.7%) and $276.66 million in FY2021 (-9.5%).
- The Q2 2026 figure stands as the lowest quarterly EBITDA since Q2 2019.
- On a year-over-year basis, EBITDA increased in four of the last eight quarters, with an average decline of 3.7%.
- The strongest year-over-year quarter for EBITDA in the past five years was Q2 2023, with growth of 66.3%; the weakest was Q2 2026, with a decline of 69.5%.
- According to Business Quant data, EBITDA for the three prior quarters was $131.6 million (Q1 2026), $135.87 million (Q4 2025) and $137.8 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 308.22 Bn | 266.74 Bn | 5.02 Bn | -6.39 Bn |
| 2 | Rtx | 256.81 Bn | 225.08 Bn | 5.81 Bn | 4.41 Bn |
| 3 | Boeing | 152.21 Bn | 58.90 Bn | 2.41 Bn | 752.00 Mn |
| 4 | Lockheed Martin | 126.07 Bn | 112.79 Bn | 2.45 Bn | 2.88 Bn |
| 5 | General Dynamics | 93.38 Bn | 80.49 Bn | 2.18 Bn | 1.68 Bn |
| 6 | Howmet Aerospace | 82.34 Bn | 77.94 Bn | 951.00 Mn | 795.00 Mn |
| 7 | Motorola Solutions | 77.30 Bn | 73.65 Bn | 1.68 Bn | 957.00 Mn |
| 8 | Northrop Grumman | 76.71 Bn | 64.17 Bn | 2.35 Bn | 1.65 Bn |
| 9 | Honeywell International | 68.23 Bn | 20.35 Bn | 3.65 Bn | 2.10 Bn |
| 10 | Parsons | 4.85 Bn | 3.41 Bn | 295.24 Mn | 39.17 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 39.17 Mn |
| Mar 31, 2026 | 132.81 Mn |
| Dec 31, 2025 | 137.09 Mn |
| Sep 30, 2025 | 139.03 Mn |
| Jun 30, 2025 | 125.64 Mn |
| Mar 31, 2025 | 137.86 Mn |
| Dec 31, 2024 | 126.79 Mn |
| Sep 30, 2024 | 140.77 Mn |
| Jun 30, 2024 | 137.09 Mn |
| Mar 31, 2024 | 130.47 Mn |
| Dec 31, 2023 | 110.93 Mn |
| Sep 30, 2023 | 114.20 Mn |
| Jun 30, 2023 | 105.89 Mn |
| Mar 31, 2023 | 80.15 Mn |
| Dec 31, 2022 | 84.24 Mn |
| Sep 30, 2022 | 94.25 Mn |
| Jun 30, 2022 | 63.86 Mn |
| Mar 31, 2022 | 66.85 Mn |
| Dec 31, 2021 | 85.18 Mn |
| Sep 30, 2021 | 77.61 Mn |
Parsons 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=PSN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "PSN", "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=PSN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();