Prenetics Global (PRE) Net Cash Flow (2025 - 2026)
Prenetics Global (PRE) reported Net Cash Flow of $3.03 million for Q2 2026, compared with -$25.61 million a year earlier and down 87.4% from the prior quarter.
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Analysis
Prenetics Global (PRE) Net Cash Flow (2025 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Prenetics Global's Net Cash Flow came in at -$17.41 million; for FY2025, it came in at -$41.14 million.
- By year, Net Cash Flow came in at $6.32 million in FY2024, -$101.42 million in FY2023, $111.69 million in FY2022 (+439.2%) and $20.71 million in FY2021 (+593.1%).
- Five-year quarterly Net Cash Flow spans a low of -$101.42 million in Q4 2023 and a high of $24.03 million in Q1 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | NCF (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 248.62 Bn | 227.65 Bn | 4.88 Bn | 718.00 Mn |
| 2 | Abbott Laboratories | 179.72 Bn | 150.15 Bn | 7.27 Bn | -1.70 Bn |
| 3 | Danaher | 160.69 Bn | 144.50 Bn | 3.61 Bn | -1.34 Bn |
| 4 | Intuitive Surgical | 158.63 Bn | 138.92 Bn | 2.08 Bn | 228.30 Mn |
| 5 | Medtronic | 122.80 Bn | 88.05 Bn | 6.34 Bn | -169.00 Mn |
| 6 | Stryker | 117.90 Bn | 104.01 Bn | 4.50 Bn | 527.00 Mn |
| 7 | Boston Scientific | 66.70 Bn | 61.46 Bn | 3.85 Bn | -892.00 Mn |
| 8 | Becton Dickinson | 54.67 Bn | 51.82 Bn | 2.32 Bn | -42.00 Mn |
| 9 | Edwards Lifesciences | 51.71 Bn | 35.72 Bn | 1.35 Bn | 458.40 Mn |
| 10 | Prenetics Global | 246.97 Mn | 110.79 Mn | 30.20 Mn | 3.03 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.03 Mn |
| Mar 31, 2026 | 24.03 Mn |
| Dec 31, 2025 | -15.32 Mn |
| Jun 30, 2025 | -25.61 Mn |
| Mar 31, 2025 | -4.23 Mn |
API Access
Prenetics Global Net Cash Flow 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=net-cash-flow&ticker=PRE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "net-cash-flow", "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=net-cash-flow&ticker=PRE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();