Clps (CLPS) Operating Expenses (2017 - 2018)
Clps' Operating Expenses came in at -$5.78 million for the year ended Jun 30, 2025, compared with -$4.92 million a year earlier.
Analysis
Clps (CLPS) Operating Expenses (2017 - 2018) Analysis & Trends
Going back to the year ended Jun 30, 2016, Clps' Operating Expenses data covers 10 years.
- The figure for the year ended Jun 30, 2025 represents the lowest annual Operating Expenses in data going back to the year ended Jun 30, 2016.
- Per Business Quant, earlier years put Operating Expenses at -$4.92 million in the year ended Jun 30, 2024, -$4.95 million in the year ended Jun 30, 2023, -$5.21 million in the year ended Jun 30, 2022 and -$4.8 million in the year ended Jun 30, 2021.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 822.22 Mn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 12.44 Mn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 747.88 Mn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 634.01 Mn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 722.71 Mn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Clps | 30.64 Mn | -3.32 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2018 | 4.37 Mn |
| Mar 31, 2018 | 3.80 Mn |
| Jun 30, 2017 | 3.14 Mn |
| Mar 31, 2017 | 2.63 Mn |
API Access
Clps Operating 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=operating-expenses&ticker=CLPS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CLPS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=CLPS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();