Prenetics Global (PRE) Total Liabilities (2021 - 2026)
Prenetics Global (PRE) reported Total Liabilities of $60.73 million for Q2 2026, up 26.0% from $48.21 million a year earlier and up 11.9% from the prior quarter.
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Analysis
Prenetics Global (PRE) Total Liabilities (2021 - 2026) Analysis & Trends
At the end of FY2025, Prenetics Global posted Total Liabilities of $49.61 million, up 14.9% from FY2024.
- Total Liabilities has a four-year compound annual growth rate of -45.2% (FY2021 to FY2025).
- By year, Total Liabilities came in at $43.19 million in FY2024 (-9.7%), $47.81 million in FY2023 (-36.3%), $75.07 million in FY2022 (-86.3%) and $549.32 million in FY2021.
- The Q2 2026 figure ranks as the highest quarterly Total Liabilities since Q4 2022.
- Year over year, Total Liabilities gained in five of the last eight quarters, with an average decline of 12.1%.
- The high point for year-over-year Total Liabilities in five years was Q2 2026 (growth of 26.0%); the low point was Q4 2024 (a decline of 96.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $54.28 million (Q1 2026), $838,397 (Q4 2025) and $35.31 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 265.71 Bn | 242.23 Bn | 5.13 Bn | 59.47 Bn |
| 2 | Abbott Laboratories | 189.37 Bn | 163.23 Bn | 7.39 Bn | 56.62 Bn |
| 3 | Danaher | 164.78 Bn | 144.43 Bn | 3.84 Bn | 39.65 Bn |
| 4 | Intuitive Surgical | 157.85 Bn | 138.13 Bn | 2.08 Bn | 3.23 Bn |
| 5 | Medtronic | 129.66 Bn | 94.91 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 121.82 Bn | 108.01 Bn | 4.25 Bn | 23.79 Bn |
| 7 | Boston Scientific | 63.42 Bn | 58.86 Bn | 3.43 Bn | 19.59 Bn |
| 8 | Edwards Lifesciences | 59.49 Bn | 42.69 Bn | 1.35 Bn | 3.18 Bn |
| 9 | Becton Dickinson | 58.38 Bn | 55.53 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Prenetics Global | 251.88 Mn | -36.68 Mn | - | 838,397.23 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 60.73 Mn |
| Mar 31, 2026 | 54.28 Mn |
| Dec 31, 2025 | 838,397.23 |
| Sep 30, 2025 | 35.31 Mn |
| Jun 30, 2025 | 48.21 Mn |
| Mar 31, 2025 | 45.10 Mn |
| Dec 31, 2024 | 1.73 Mn |
| Sep 30, 2024 | 55.67 Mn |
| Jun 30, 2024 | 42.30 Mn |
| Mar 31, 2024 | 40.82 Mn |
| Dec 31, 2023 | 47.81 Mn |
| Sep 30, 2023 | 47.63 Mn |
| Jun 30, 2023 | 60.62 Mn |
| Mar 31, 2023 | 57.51 Mn |
| Dec 31, 2022 | 75.07 Mn |
| Sep 30, 2022 | 62.33 Mn |
| Jun 30, 2022 | 59.24 Mn |
| Mar 31, 2022 | 594.61 Mn |
| Dec 31, 2021 | 549.32 Mn |
API Access
Prenetics Global Total 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-liabilities&ticker=PRE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PRE", "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-liabilities&ticker=PRE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();