Wrap Technologies (WRAP) Operating Expenses (2017 - 2026)
Wrap Technologies' Operating Expenses was $3.8 million in Q2 2026, up 13.6% from $3.34 million a year earlier but down 30.5% from the prior quarter.
Wrap Technologies (WRAP) Operating Expenses (2017 - 2026) Analysis & Trends
On a trailing twelve-month basis, Wrap Technologies' Operating Expenses was $17.58 million through Jun 30, 2026, up 4.9% year-over-year; for FY2025, it came in at $16.18 million, down 10.2% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 2.3% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $18.03 million in FY2024 (-16.6%), $21.63 million in FY2023 (+0.8%), $21.46 million in FY2022 (-19.0%) and $26.49 million in FY2021 (+83.7%).
- Quarterly Operating Expenses has moved between $3.34 million (Q2 2025) and $6.73 million (Q3 2021) over five years.
- Compared with a year earlier, Operating Expenses was higher in two of the last eight quarters, with an average decline of 6.2%.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2021 (growth of 60.9%); the worst was Q2 2022 (a decline of 32.3%).
- Per Business Quant data, WRAP's Operating Expenses in the three quarters before Q2 2026 was $5.46 million (Q1 2026), $4.68 million (Q4 2025) and $3.64 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 330.21 Bn | 284.21 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 252.88 Bn | 226.09 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 145.76 Bn | 52.46 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 119.56 Bn | 106.28 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 91.38 Bn | 86.98 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 90.40 Bn | 77.51 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 74.81 Bn | 71.18 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 71.85 Bn | 61.10 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 67.04 Bn | 19.48 Bn | 3.65 Bn | 1.87 Bn |
| 10 | Wrap Technologies | 74.85 Mn | 53.37 Mn | 1.55 Mn | 3.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.80 Mn |
| Mar 31, 2026 | 5.46 Mn |
| Dec 31, 2025 | 4.68 Mn |
| Sep 30, 2025 | 3.64 Mn |
| Jun 30, 2025 | 3.34 Mn |
| Mar 31, 2025 | 4.52 Mn |
| Dec 31, 2024 | 5.04 Mn |
| Sep 30, 2024 | 3.86 Mn |
| Jun 30, 2024 | 4.15 Mn |
| Mar 31, 2024 | 4.98 Mn |
| Dec 31, 2023 | 6.34 Mn |
| Sep 30, 2023 | 4.93 Mn |
| Jun 30, 2023 | 5.75 Mn |
| Mar 31, 2023 | 4.61 Mn |
| Dec 31, 2022 | 5.30 Mn |
| Sep 30, 2022 | 4.82 Mn |
| Jun 30, 2022 | 5.24 Mn |
| Mar 31, 2022 | 6.10 Mn |
| Dec 31, 2021 | 5.98 Mn |
| Sep 30, 2021 | 6.73 Mn |
Wrap 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=WRAP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WRAP", "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=WRAP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();