Cyberloq Technologies (CLOQ) Operating Expenses (2011 - 2026)
Cyberloq Technologies (CLOQ) posted Operating Expenses of $115,283 for Q2 2026, down 29.4% from $163,269 a year earlier and down 37.7% from the prior quarter.
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Analysis
Cyberloq Technologies (CLOQ) Operating Expenses (2011 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Cyberloq Technologies was $641,644, down 22.2% year-over-year; for FY2025, it came in at $771,616, up 0.5% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of -2.6% (FY2020 to FY2025).
- In prior years, Cyberloq Technologies' Operating Expenses was $767,929 in FY2024 (+100.4%), $383,243 in FY2023 (-44.1%), $685,088 in FY2022 (-35.4%) and $1.06 million in FY2021 (+20.4%).
- The Q2 2026 figure stands as the lowest quarterly Operating Expenses since Q4 2023.
- On a year-over-year basis, Operating Expenses has declined in each of the last three quarters, with growth averaging 18.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2022, with growth of 195.2%; the weakest was Q4 2022, with a decline of 78.5%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $185,008 (Q1 2026), $190,058 (Q4 2025) and $151,295 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 316.55 Bn | 301.63 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 269.03 Bn | 249.47 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 129.08 Bn | 115.01 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 116.42 Bn | 103.73 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 96.40 Bn | 78.04 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Okta | 34.24 Bn | 24.34 Bn | 641.00 Mn | 534.00 Mn |
| 7 | Axon Enterprise | 34.08 Bn | 28.61 Bn | 546.45 Mn | 499.67 Mn |
| 8 | Zscaler | 32.34 Bn | 18.46 Bn | - | - |
| 9 | Baidu | 29.50 Bn | -44.13 Bn | 1.47 Mn | 4.17 Bn |
| 10 | Cyberloq Technologies | 21.20 Mn | 20.77 Mn | - | 115,283.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 115,283.00 |
| Mar 31, 2026 | 185,008.00 |
| Dec 31, 2025 | 190,058.00 |
| Sep 30, 2025 | 151,295.00 |
| Jun 30, 2025 | 163,269.00 |
| Mar 31, 2025 | 266,992.00 |
| Dec 31, 2024 | 250,510.00 |
| Sep 30, 2024 | 144,365.00 |
| Jun 30, 2024 | 162,020.00 |
| Mar 31, 2024 | 211,035.00 |
| Dec 31, 2023 | 110,647.00 |
| Sep 30, 2023 | 81,422.00 |
| Jun 30, 2023 | 93,468.00 |
| Mar 31, 2023 | 97,707.00 |
| Dec 31, 2022 | 105,659.00 |
| Sep 30, 2022 | 112,664.00 |
| Jun 30, 2022 | 190,549.00 |
| Mar 31, 2022 | 276,215.00 |
| Dec 31, 2021 | 491,453.00 |
| Sep 30, 2021 | 279,261.00 |
API Access
Cyberloq Technologies 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=CLOQ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CLOQ", "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=CLOQ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();