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.
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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 | 51.23 Bn | 37.72 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 31.84 Bn | 25.00 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Wipro | 20.59 Bn | 15.29 Bn | 738.00 Mn | 2.23 Bn |
| 4 | Cdw | 19.60 Bn | 17.59 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Td Synnex | 19.55 Bn | 13.70 Bn | 1.43 Bn | 784.64 Mn |
| 6 | Cgi | 17.25 Bn | 15.05 Bn | - | - |
| 7 | Arrow Electronics | 10.82 Bn | 9.77 Bn | 1.13 Bn | 747.88 Mn |
| 8 | Avnet | 7.36 Bn | 6.54 Bn | 865.03 Mn | 634.01 Mn |
| 9 | EPAM Systems | 6.76 Bn | 2.40 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Clps | 30.34 Mn | -329.42 Mn | - | - |
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_KEYimport 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();