Polaris (PII) Change in Accured Expenses (2009 - 2026)
Polaris (PII) recorded Change in Accured Expenses of -$34.1 million in Q2 2026, compared with $134.1 million a year earlier.
Polaris (PII) Change in Accured Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Polaris' Change in Accured Expenses came in at -$16.1 million as of Jun 30, 2026; for FY2025, it came in at $137.4 million, down 13.5% from FY2024.
- Annual Change in Accured Expenses has a five-year compound annual growth rate of 26.5% (FY2020 to FY2025).
- Across earlier years, Change in Accured Expenses came in at $158.8 million in FY2024 (-26.9%), $217.1 million in FY2023 (+65.6%), $131.1 million in FY2022 and -$62.3 million in FY2021.
- Quarterly Change in Accured Expenses has ranged from -$159.2 million in Q1 2022 to $210 million in Q4 2024 over the past five years.
- Peak year-over-year performance for Change in Accured Expenses in the last five years was growth of 181.9% in Q4 2022, against a decline of 93.5% in Q3 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at -$137.1 million (Q1 2026), $137.5 million (Q4 2025) and $17.6 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,199.60 Bn | 1,034.16 Bn | 4.75 Bn | 1.94 Bn |
| 2 | Toyota Motor | 237.87 Bn | -168.87 Bn | 20.95 Bn | - |
| 3 | Ferrari | 144.10 Bn | 136.55 Bn | 1.18 Bn | 19.87 Mn |
| 4 | Honda Motor | 142.11 Bn | 9.49 Bn | 8.46 Bn | -839.67 Mn |
| 5 | General Motors | 68.70 Bn | -36.17 Bn | 7.33 Bn | - |
| 6 | Ford Motor | 47.39 Bn | -95.07 Bn | 6.08 Bn | 1.78 Bn |
| 7 | Rivian Automotive | 19.48 Bn | -3.81 Bn | 179.00 Mn | 190.00 Mn |
| 8 | Magna International | 18.09 Bn | 15.65 Bn | 1.61 Bn | - |
| 9 | Stellantis | 12.78 Bn | -153.22 Bn | 5.55 Bn | - |
| 10 | Polaris | 3.06 Bn | 2.00 Bn | - | -34.10 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -34.10 Mn |
| Mar 31, 2026 | -137.10 Mn |
| Dec 31, 2025 | 137.50 Mn |
| Sep 30, 2025 | 17.60 Mn |
| Jun 30, 2025 | 134.10 Mn |
| Mar 31, 2025 | -151.80 Mn |
| Dec 31, 2024 | 210.00 Mn |
| Sep 30, 2024 | -30.70 Mn |
| Jun 30, 2024 | 107.50 Mn |
| Mar 31, 2024 | -128.00 Mn |
| Dec 31, 2023 | 145.30 Mn |
| Sep 30, 2023 | 38.90 Mn |
| Jun 30, 2023 | 98.10 Mn |
| Mar 31, 2023 | -65.20 Mn |
| Dec 31, 2022 | 118.70 Mn |
| Sep 30, 2022 | 90.20 Mn |
| Jun 30, 2022 | 81.40 Mn |
| Mar 31, 2022 | -159.20 Mn |
| Dec 31, 2021 | 42.10 Mn |
| Sep 30, 2021 | 3.80 Mn |
Polaris Change in Accured 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=PII&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "PII", "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=PII&period=max&api_key=YOUR_API_KEY");
const data = await res.json();