Xpel (XPEL) Total Non-Current Liabilities (2019 - 2026)
Xpel (XPEL) posted Total Non-Current Liabilities of $143.77 million for Q2 2026, up 136.0% from $60.92 million a year earlier and up 55.8% from the prior quarter.
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Analysis
Xpel (XPEL) Total Non-Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Xpel's Total Non-Current Liabilities came in at $87.83 million, up 50.5% from FY2024.
- Annual Total Non-Current Liabilities shows a five-year compound annual growth rate of 24.2% (FY2020 to FY2025).
- In prior years, Xpel's Total Non-Current Liabilities was $58.34 million in FY2024 (-18.0%), $71.16 million in FY2023 (+5.3%), $67.57 million in FY2022 (-8.6%) and $73.92 million in FY2021 (+148.7%).
- The Q2 2026 figure stands as the highest quarterly Total Non-Current Liabilities in data going back to Q4 2019.
- On a year-over-year basis, Total Non-Current Liabilities has increased in each of the last five quarters, with growth averaging 36.5% over the last eight quarters.
- The strongest year-over-year quarter for Total Non-Current Liabilities in the past five years was Q1 2022, with growth of 170.2%; the weakest was Q2 2023, with a decline of 26.7%.
- According to Business Quant data, Total Non-Current Liabilities for the three prior quarters was $92.3 million (Q1 2026), $87.83 million (Q4 2025) and $101.21 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,148.52 Bn | 983.08 Bn | 4.75 Bn | 47.48 Bn |
| 2 | Toyota Motor | 242.17 Bn | -164.57 Bn | 20.95 Bn | 3.42 Bn |
| 3 | Ferrari | 145.86 Bn | 138.30 Bn | 1.18 Bn | 5.63 Bn |
| 4 | Honda Motor | 143.38 Bn | 10.76 Bn | 8.46 Bn | 5.36 Bn |
| 5 | General Motors | 67.56 Bn | -37.30 Bn | 7.33 Bn | 122.27 Bn |
| 6 | Ford Motor | 47.24 Bn | -95.23 Bn | 6.08 Bn | 219.21 Bn |
| 7 | Rivian Automotive | 20.35 Bn | -2.94 Bn | 179.00 Mn | 8.76 Bn |
| 8 | Magna International | 17.85 Bn | 15.41 Bn | 1.61 Bn | - |
| 9 | Stellantis | 12.63 Bn | -153.36 Bn | 5.55 Bn | 74.97 Bn |
| 10 | Xpel | 1.22 Bn | 1.03 Bn | 63.14 Mn | 143.77 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 143.77 Mn |
| Mar 31, 2026 | 92.30 Mn |
| Dec 31, 2025 | 87.83 Mn |
| Sep 30, 2025 | 101.21 Mn |
| Jun 30, 2025 | 60.92 Mn |
| Mar 31, 2025 | 57.54 Mn |
| Dec 31, 2024 | 58.34 Mn |
| Sep 30, 2024 | 53.24 Mn |
| Jun 30, 2024 | 59.40 Mn |
| Mar 31, 2024 | 71.39 Mn |
| Dec 31, 2023 | 71.16 Mn |
| Sep 30, 2023 | 59.27 Mn |
| Jun 30, 2023 | 62.18 Mn |
| Mar 31, 2023 | 69.81 Mn |
| Dec 31, 2022 | 67.57 Mn |
| Sep 30, 2022 | 72.41 Mn |
| Jun 30, 2022 | 84.84 Mn |
| Mar 31, 2022 | 93.59 Mn |
| Dec 31, 2021 | 73.92 Mn |
| Sep 30, 2021 | 45.28 Mn |
API Access
Xpel Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=XPEL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "XPEL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=XPEL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();