Parsons (PSN) Accumulated Expenses (2018 - 2026)
Parsons' Accumulated Expenses was $940.53 million in Q2 2026, up 10.9% from $847.85 million a year earlier and up 13.1% from the prior quarter.
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Analysis
Parsons (PSN) Accumulated Expenses (2018 - 2026) Analysis & Trends
At the end of FY2025, Accumulated Expenses at Parsons came in at $884.45 million, down 1.1% from FY2024.
- Accumulated Expenses shows a five-year compound annual growth rate of 6.3% (FY2020 to FY2025).
- In earlier years, Accumulated Expenses was $894.43 million in FY2024 (+11.6%), $801.42 million in FY2023 (+27.2%), $630.19 million in FY2022 (+5.2%) and $599.09 million in FY2021 (-7.9%).
- The Q2 2026 figure marks the highest quarterly Accumulated Expenses in data going back to Q4 2018.
- Compared with a year earlier, Accumulated Expenses was higher in seven of the last eight quarters, with growth averaging 6.8%.
- The best year-over-year quarter for Accumulated Expenses over five years was Q4 2023 (growth of 27.2%); the worst was Q3 2021 (a decline of 13.7%).
- Per Business Quant data, PSN's Accumulated Expenses in the three quarters before Q2 2026 was $831.53 million (Q1 2026), $884.45 million (Q4 2025) and $912.14 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 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 |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn |
| 10 | Parsons | 4.39 Bn | 3.06 Bn | 295.24 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 940.53 Mn |
| Mar 31, 2026 | 831.53 Mn |
| Dec 31, 2025 | 884.45 Mn |
| Sep 30, 2025 | 912.14 Mn |
| Jun 30, 2025 | 847.85 Mn |
| Mar 31, 2025 | 783.69 Mn |
| Dec 31, 2024 | 894.43 Mn |
| Sep 30, 2024 | 876.58 Mn |
| Jun 30, 2024 | 822.12 Mn |
| Mar 31, 2024 | 739.21 Mn |
| Dec 31, 2023 | 801.42 Mn |
| Sep 30, 2023 | 771.91 Mn |
| Jun 30, 2023 | 693.66 Mn |
| Mar 31, 2023 | 635.09 Mn |
| Dec 31, 2022 | 630.19 Mn |
| Sep 30, 2022 | 682.68 Mn |
| Jun 30, 2022 | 647.04 Mn |
| Mar 31, 2022 | 609.10 Mn |
| Dec 31, 2021 | 599.09 Mn |
| Sep 30, 2021 | 626.17 Mn |
API Access
Parsons 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=PSN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "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=accumulated-expenses&ticker=PSN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();