Pc Connection (CNXN) Accumulated Expenses (2010 - 2026)
Pc Connection (CNXN) posted Accumulated Expenses of $46.79 million for Q2 2026, up 13.9% from $41.08 million a year earlier but down 11.0% from the prior quarter.
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Analysis
Pc Connection (CNXN) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2025, Pc Connection's Accumulated Expenses came in at $51.25 million, up 7.6% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of -2.3% (FY2020 to FY2025).
- In prior years, Pc Connection's Accumulated Expenses was $47.63 million in FY2024 (+8.6%), $43.84 million in FY2023 (-18.5%), $53.81 million in FY2022 (-13.0%) and $61.83 million in FY2021 (+7.4%).
- Quarterly Accumulated Expenses has run from a low of $40.79 million in Q3 2025 to a high of $71.55 million in Q1 2022 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last three quarters, with growth averaging 0.7% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q3 2021, with growth of 49.3%; the weakest was Q1 2023, with a decline of 23.2%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $52.58 million (Q1 2026), $51.25 million (Q4 2025) and $40.79 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Infosys | 44.69 Bn | 44.75 Bn | 1.60 Bn |
| 2 | Cognizant Technology Solutions | 26.45 Bn | 19.61 Bn | 1.83 Bn |
| 3 | Td Synnex | 22.21 Bn | 16.36 Bn | 1.43 Bn |
| 4 | Cdw | 16.70 Bn | 14.69 Bn | 1.32 Bn |
| 5 | Cgi | 15.63 Bn | 13.41 Bn | - |
| 6 | Arrow Electronics | 12.33 Bn | 11.35 Bn | 1.13 Bn |
| 7 | Avnet | 8.78 Bn | 7.96 Bn | 865.03 Mn |
| 8 | Ingram Micro Holding | 6.70 Bn | 2.31 Bn | 958.68 Mn |
| 9 | EPAM Systems | 5.58 Bn | 1.22 Bn | 429.57 Mn |
| 10 | Pc Connection | 2.33 Bn | 773.48 Mn | 157.47 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 46.79 Mn |
| Mar 31, 2026 | 52.58 Mn |
| Dec 31, 2025 | 51.25 Mn |
| Sep 30, 2025 | 40.79 Mn |
| Jun 30, 2025 | 41.08 Mn |
| Mar 31, 2025 | 52.04 Mn |
| Dec 31, 2024 | 47.63 Mn |
| Sep 30, 2024 | 46.16 Mn |
| Jun 30, 2024 | 48.53 Mn |
| Mar 31, 2024 | 48.40 Mn |
| Dec 31, 2023 | 43.84 Mn |
| Sep 30, 2023 | 49.10 Mn |
| Jun 30, 2023 | 49.81 Mn |
| Mar 31, 2023 | 54.95 Mn |
| Dec 31, 2022 | 53.81 Mn |
| Sep 30, 2022 | 62.85 Mn |
| Jun 30, 2022 | 57.08 Mn |
| Mar 31, 2022 | 71.55 Mn |
| Dec 31, 2021 | 61.83 Mn |
| Sep 30, 2021 | 52.24 Mn |
API Access
Pc Connection 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=CNXN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=CNXN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();