DarkPulse (DPLS) Change in Accrued Expenses (2009 - 2026)
DarkPulse's Change in Accured Expenses came in at $129,883 for Q2 2026, down 86.6% from $972,313 a year earlier but up 15.3% from the prior quarter.
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Analysis
DarkPulse (DPLS) Change in Accrued Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, DarkPulse reported Change in Accured Expenses of $953,306, down 41.0% year-over-year; for FY2025, it was $1.95 million, up 43.2% from FY2024.
- Change in Accured Expenses carries a five-year compound annual growth rate of 48.5% (FY2020 to FY2025).
- Going back by year, Change in Accured Expenses was $1.36 million in FY2024 (-71.7%), $4.8 million in FY2023, -$2.61 million in FY2022 and -$2.04 million in FY2021.
- The five-year range for quarterly Change in Accured Expenses is -$4.25 million (Q3 2021) to $2.53 million (Q4 2023).
- Year-over-year, Change in Accured Expenses increased in 1 of the last four quarters, with an average decline of 26.3%.
- The fastest year-over-year change in Change in Accured Expenses over five years came in Q4 2023 (growth of 645.1%), and the weakest in Q2 2026 (a decline of 86.6%).
- Business Quant data shows DPLS's Change in Accured Expenses at $112,696 (Q1 2026), $792,838 (Q4 2025) and -$82,111 (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 172.92 Bn | 132.01 Bn | 5.98 Bn | 529.75 Mn |
| 2 | Cintas | 90.00 Bn | 89.09 Bn | 1.55 Bn | -77.80 Mn |
| 3 | Iron Mountain | 32.99 Bn | 32.50 Bn | 1.06 Bn | -148.01 Mn |
| 4 | Rollins | 18.37 Bn | 17.91 Bn | 582.90 Mn | 32.99 Mn |
| 5 | APi | 18.18 Bn | 15.39 Bn | 770.00 Mn | - |
| 6 | UL Solutions | 16.47 Bn | 14.51 Bn | 423.00 Mn | 52.00 Mn |
| 7 | Aramark | 14.29 Bn | 12.30 Bn | 430.34 Mn | -6.96 Mn |
| 8 | Rentokil Initial | 11.99 Bn | 5.51 Bn | - | - |
| 9 | Gartner | 11.92 Bn | 5.41 Bn | 1.07 Bn | 7.27 Mn |
| 10 | DarkPulse | 1.45 Mn | 2.45 Mn | 11,985.00 | 129,883.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 129,883.00 |
| Mar 31, 2026 | 112,696.00 |
| Dec 31, 2025 | 792,838.00 |
| Sep 30, 2025 | -82,111.00 |
| Jun 30, 2025 | 972,313.00 |
| Mar 31, 2025 | 266,803.00 |
| Dec 31, 2024 | -821,223.00 |
| Sep 30, 2024 | 1.20 Mn |
| Jun 30, 2024 | 545,967.00 |
| Mar 31, 2024 | 437,569.00 |
| Dec 31, 2023 | 2.53 Mn |
| Sep 30, 2023 | -427,108.00 |
| Jun 30, 2023 | 1.91 Mn |
| Mar 31, 2023 | 785,475.00 |
| Dec 31, 2022 | 339,515.00 |
| Sep 30, 2022 | 171,016.00 |
| Jun 30, 2022 | -4.10 Mn |
| Mar 31, 2022 | 978,303.00 |
| Dec 31, 2021 | 2.32 Mn |
| Sep 30, 2021 | -4.25 Mn |
API Access
DarkPulse Change in Accrued 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=DPLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "DPLS", "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=DPLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();