Xpel (XPEL) Non-Current Assets (2018 - 2026)
Xpel (XPEL) reported Non-Current Assets of $245.75 million for Q2 2026, up 103.5% from $120.76 million a year earlier and up 56.3% from the prior quarter.
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Analysis
Xpel (XPEL) Non-Current Assets (2018 - 2026) Analysis & Trends
At the end of FY2025, Xpel posted Non-Current Assets of $151.83 million, up 29.5% from FY2024.
- Non-Current Assets has increased for seven consecutive years, with a five-year compound annual growth rate of 48.4% (FY2020 to FY2025).
- By year, Non-Current Assets came in at $117.26 million in FY2024 (+11.1%), $105.59 million in FY2023 (+22.0%), $86.54 million in FY2022 (+5.6%) and $81.99 million in FY2021 (+289.3%).
- The Q2 2026 figure ranks as the highest quarterly Non-Current Assets in data going back to Q4 2018.
- Year over year, Non-Current Assets has now increased in each of the last 25 quarters, with growth averaging 32.3% over the last eight quarters.
- Across the past five years, year-over-year growth in Non-Current Assets ran from 3.7% in Q1 2023 to 289.3% in Q4 2021.
- Per Business Quant data, the three quarters before Q2 2026 came in at $157.25 million (Q1 2026), $151.83 million (Q4 2025) and $153.16 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non-Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,148.52 Bn | 983.08 Bn | 4.75 Bn | 79.77 Bn |
| 2 | Toyota Motor | 242.17 Bn | -164.57 Bn | 20.95 Bn | 400.16 Bn |
| 3 | Ferrari | 145.86 Bn | 138.30 Bn | 1.18 Bn | 5.81 Bn |
| 4 | Honda Motor | 143.38 Bn | 10.76 Bn | 8.46 Bn | 132.91 Bn |
| 5 | General Motors | 67.56 Bn | -37.30 Bn | 7.33 Bn | 172.73 Bn |
| 6 | Ford Motor | 47.24 Bn | -95.23 Bn | 6.08 Bn | 168.04 Bn |
| 7 | Rivian Automotive | 20.35 Bn | -2.94 Bn | 179.00 Mn | 7.52 Bn |
| 8 | Magna International | 17.85 Bn | 15.41 Bn | 1.61 Bn | - |
| 9 | Stellantis | 12.63 Bn | -153.36 Bn | 5.55 Bn | 143.02 Bn |
| 10 | Xpel | 1.22 Bn | 1.03 Bn | 63.14 Mn | 245.75 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 245.75 Mn |
| Mar 31, 2026 | 157.25 Mn |
| Dec 31, 2025 | 151.83 Mn |
| Sep 30, 2025 | 153.16 Mn |
| Jun 30, 2025 | 120.76 Mn |
| Mar 31, 2025 | 116.52 Mn |
| Dec 31, 2024 | 117.26 Mn |
| Sep 30, 2024 | 114.32 Mn |
| Jun 30, 2024 | 113.92 Mn |
| Mar 31, 2024 | 105.56 Mn |
| Dec 31, 2023 | 105.59 Mn |
| Sep 30, 2023 | 88.74 Mn |
| Jun 30, 2023 | 91.01 Mn |
| Mar 31, 2023 | 87.36 Mn |
| Dec 31, 2022 | 86.54 Mn |
| Sep 30, 2022 | 83.62 Mn |
| Jun 30, 2022 | 81.49 Mn |
| Mar 31, 2022 | 84.25 Mn |
| Dec 31, 2021 | 81.99 Mn |
| Sep 30, 2021 | 58.41 Mn |
API Access
Xpel Non-Current Assets 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=non-current-assets&ticker=XPEL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-assets", "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=non-current-assets&ticker=XPEL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();