Pc Connection (CNXN) Change in Accured Expenses (2010 - 2026)
Pc Connection's Change in Accured Expenses was -$8.17 million in Q2 2026, compared with -$14.63 million a year earlier.
Pc Connection (CNXN) Change in Accured Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Pc Connection's Change in Accured Expenses was $8.32 million through Jun 30, 2026; for FY2025, it was $10.71 million, up 78.9% from FY2024.
- Change in Accured Expenses shows a five-year compound annual growth rate of 0.3% (FY2020 to FY2025).
- In earlier years, Change in Accured Expenses was $5.98 million in FY2024, -$11.79 million in FY2023, -$14.73 million in FY2022 and $17.73 million in FY2021 (+68.3%).
- Quarterly Change in Accured Expenses has moved between -$16.16 million (Q4 2022) and $11.19 million (Q4 2025) over five years.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q1 2022 (growth of 240.9%); the worst was Q1 2023 (a decline of 53.2%).
- Per Business Quant data, CNXN's Change in Accured Expenses in the three quarters before Q2 2026 was -$1.08 million (Q1 2026), $11.19 million (Q4 2025) and $6.38 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | - |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | - |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | - |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | - |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | - |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 105.67 Mn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 100.83 Mn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | -86.93 Mn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | -67.67 Mn |
| 10 | Pc Connection | 2.26 Bn | 705.84 Mn | 157.47 Mn | -8.17 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -8.17 Mn |
| Mar 31, 2026 | -1.08 Mn |
| Dec 31, 2025 | 11.19 Mn |
| Sep 30, 2025 | 6.38 Mn |
| Jun 30, 2025 | -14.63 Mn |
| Mar 31, 2025 | 7.76 Mn |
| Dec 31, 2024 | -3.66 Mn |
| Sep 30, 2024 | 3.46 Mn |
| Jun 30, 2024 | 172,000.00 |
| Mar 31, 2024 | 6.02 Mn |
| Dec 31, 2023 | -11.07 Mn |
| Sep 30, 2023 | 5.64 Mn |
| Jun 30, 2023 | -8.81 Mn |
| Mar 31, 2023 | 2.45 Mn |
| Dec 31, 2022 | -16.16 Mn |
| Sep 30, 2022 | 6.01 Mn |
| Jun 30, 2022 | -9.80 Mn |
| Mar 31, 2022 | 5.23 Mn |
| Dec 31, 2021 | 8.29 Mn |
| Sep 30, 2021 | 4.09 Mn |
Pc Connection 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=CNXN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "CNXN", "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=CNXN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();