Polar Power (POLA) Operating Expenses (2018 - 2026)
Polar Power (POLA) recorded Operating Expenses of $1.33 million in Q2 2026, up 28.3% from $1.04 million a year earlier and up 20.1% from the prior quarter.
Polar Power (POLA) Operating Expenses (2018 - 2026) Analysis & Trends
On a TTM basis, Polar Power's Operating Expenses came in at $5.25 million as of Jun 30, 2026, up 1.0% year-over-year; for FY2025, it was $5.27 million, down 7.4% from FY2024.
- Annual Operating Expenses has declined for three straight years, with a five-year compound annual growth rate of -6.4% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $5.69 million in FY2024 (-14.9%), $6.69 million in FY2023 (-12.7%), $7.66 million in FY2022 (+17.0%) and $6.54 million in FY2021 (-10.9%).
- Quarterly Operating Expenses has ranged from $1.04 million in Q2 2025 to $2.13 million in Q3 2022 over the past five years.
- On a year-over-year basis, Operating Expenses rose in two of the last eight quarters, with an average decline of 5.9%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 51.4% in Q4 2022, against a decline of 27.7% in Q4 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $1.11 million (Q1 2026), $1.19 million (Q4 2025) and $1.62 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 73.32 Bn | 69.88 Bn | 1.90 Bn | - |
| 10 | Polar Power | 4.61 Mn | 4.20 Mn | -337,000.00 | 1.33 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.33 Mn |
| Mar 31, 2026 | 1.11 Mn |
| Dec 31, 2025 | 1.19 Mn |
| Sep 30, 2025 | 1.62 Mn |
| Jun 30, 2025 | 1.04 Mn |
| Mar 31, 2025 | 1.42 Mn |
| Dec 31, 2024 | 1.36 Mn |
| Sep 30, 2024 | 1.38 Mn |
| Jun 30, 2024 | 1.37 Mn |
| Mar 31, 2024 | 1.58 Mn |
| Dec 31, 2023 | 1.55 Mn |
| Sep 30, 2023 | 1.57 Mn |
| Jun 30, 2023 | 1.79 Mn |
| Mar 31, 2023 | 1.79 Mn |
| Dec 31, 2022 | 1.73 Mn |
| Sep 30, 2022 | 2.13 Mn |
| Jun 30, 2022 | 1.79 Mn |
| Mar 31, 2022 | 2.01 Mn |
| Dec 31, 2021 | 1.14 Mn |
| Sep 30, 2021 | 1.73 Mn |
Polar Power 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=POLA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "POLA", "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=POLA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();