Parsons (PSN) Change in Accured Expenses (2018 - 2026)
Parsons' Change in Accured Expenses came in at $90.27 million for Q2 2026, up 134.0% from $38.57 million a year earlier.
Parsons (PSN) Change in Accured Expenses (2018 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Parsons reported Change in Accured Expenses of $79.09 million; for FY2025, it came in at -$30.26 million.
- Going back by year, Change in Accured Expenses was $79.98 million in FY2024 (-51.1%), $163.44 million in FY2023, $3.88 million in FY2022 and -$74.68 million in FY2021.
- The Q2 2026 figure represents the highest quarterly Change in Accured Expenses in data going back to Q1 2018.
- Year-over-year, Change in Accured Expenses increased in two of the last six quarters, with an average decline of 1.6%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q3 2022 (growth of 147.2%), and the weakest in Q3 2021 (a decline of 84.3%).
- Business Quant data shows PSN's Change in Accured Expenses at -$75.25 million (Q1 2026), $17.3 million (Q4 2025) and $46.76 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 321.31 Bn | 275.31 Bn | 4.68 Bn | - |
| 2 | Rtx | 248.97 Bn | 222.19 Bn | 5.13 Bn | 2.10 Bn |
| 3 | Boeing | 152.99 Bn | 59.70 Bn | 2.41 Bn | 190.00 Mn |
| 4 | Lockheed Martin | 116.67 Bn | 103.39 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 92.54 Bn | 88.15 Bn | 951.00 Mn | 41.00 Mn |
| 6 | General Dynamics | 89.31 Bn | 76.42 Bn | 2.18 Bn | - |
| 7 | Motorola Solutions | 74.04 Bn | 70.40 Bn | 1.68 Bn | 82.00 Mn |
| 8 | Northrop Grumman | 67.90 Bn | 57.15 Bn | 2.12 Bn | -34.00 Mn |
| 9 | Honeywell International | 67.82 Bn | 20.27 Bn | 3.65 Bn | 895.00 Mn |
| 10 | Parsons | 4.36 Bn | 3.04 Bn | 295.24 Mn | 90.27 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 90.27 Mn |
| Mar 31, 2026 | -75.25 Mn |
| Dec 31, 2025 | 17.30 Mn |
| Sep 30, 2025 | 46.76 Mn |
| Jun 30, 2025 | 38.57 Mn |
| Mar 31, 2025 | -132.89 Mn |
| Dec 31, 2024 | 54.33 Mn |
| Sep 30, 2024 | 36.19 Mn |
| Jun 30, 2024 | 67.06 Mn |
| Mar 31, 2024 | -77.59 Mn |
| Dec 31, 2023 | 70.18 Mn |
| Sep 30, 2023 | 59.93 Mn |
| Jun 30, 2023 | 44.23 Mn |
| Mar 31, 2023 | -10.90 Mn |
| Dec 31, 2022 | -16.34 Mn |
| Sep 30, 2022 | 27.53 Mn |
| Jun 30, 2022 | -3.18 Mn |
| Mar 31, 2022 | -4.13 Mn |
| Dec 31, 2021 | 11.72 Mn |
| Sep 30, 2021 | 11.14 Mn |
Parsons Change in Accured 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=change-in-accured-expenses&ticker=PSN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-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=change-in-accured-expenses&ticker=PSN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();