Worksport (WKSP) Operating Expenses (2010 - 2026)
Worksport's Operating Expenses came in at $5.47 million for Q2 2026, up 16.4% from $4.7 million a year earlier but down 17.1% from the prior quarter.
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Analysis
Worksport (WKSP) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Worksport reported Operating Expenses of $25.99 million, up 45.7% year-over-year; for FY2025, it was $23.29 million, up 42.2% from FY2024.
- Operating Expenses has increased in each of the last six years, with a five-year compound annual growth rate of 86.5% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $16.37 million in FY2024 (+9.3%), $14.98 million in FY2023 (+16.7%), $12.83 million in FY2022 (+70.8%) and $7.51 million in FY2021 (+627.2%).
- The five-year range for quarterly Operating Expenses is $2.05 million (Q3 2021) to $7.56 million (Q4 2025).
- Year-over-year, Operating Expenses has increased for ten consecutive quarters, with growth averaging 30.8% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2021 (growth of 913.3%), and the weakest in Q4 2023 (a decline of 3.3%).
- Business Quant data shows WKSP's Operating Expenses at $6.6 million (Q1 2026), $7.56 million (Q4 2025) and $6.36 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,314.10 Bn | 1,140.12 Bn | 4.75 Bn | 4.35 Bn |
| 2 | General Motors | 74.23 Bn | -30.38 Bn | 9.28 Bn | 46.42 Bn |
| 3 | Ferrari | 71.33 Bn | 63.82 Bn | 1.18 Bn | 471.42 Mn |
| 4 | Ford Motor | 49.14 Bn | -93.36 Bn | 6.08 Bn | 47.66 Bn |
| 5 | Honda Motor | 45.30 Bn | -104.51 Bn | 8.46 Bn | 34.70 Bn |
| 6 | Toyota Motor | 25.22 Bn | -375.60 Bn | 20.95 Bn | 78.18 Bn |
| 7 | Magna International | 18.38 Bn | 12.40 Bn | 1.61 Bn | 273.20 Mn |
| 8 | Rivian Automotive | 15.57 Bn | -7.74 Bn | 179.00 Mn | 1.02 Bn |
| 9 | Stellantis | 13.68 Bn | -147.76 Bn | 3.94 Bn | 4.25 Bn |
| 10 | Worksport | 3.75 Mn | -7.68 Mn | 1.65 Mn | 5.47 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.47 Mn |
| Mar 31, 2026 | 6.60 Mn |
| Dec 31, 2025 | 7.56 Mn |
| Sep 30, 2025 | 6.36 Mn |
| Jun 30, 2025 | 4.70 Mn |
| Mar 31, 2025 | 4.65 Mn |
| Dec 31, 2024 | 4.33 Mn |
| Sep 30, 2024 | 4.15 Mn |
| Jun 30, 2024 | 4.21 Mn |
| Mar 31, 2024 | 3.68 Mn |
| Dec 31, 2023 | 3.64 Mn |
| Sep 30, 2023 | 4.01 Mn |
| Jun 30, 2023 | 3.79 Mn |
| Mar 31, 2023 | 3.54 Mn |
| Dec 31, 2022 | 3.77 Mn |
| Sep 30, 2022 | 2.95 Mn |
| Jun 30, 2022 | 3.31 Mn |
| Mar 31, 2022 | 2.81 Mn |
| Dec 31, 2021 | 3.66 Mn |
| Sep 30, 2021 | 2.05 Mn |
API Access
Worksport 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=WKSP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WKSP", "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=WKSP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();