Edap Tms (FOCL) Total Liabilities (2009 - 2026)
Edap Tms' Total Liabilities was $77.77 million in Q2 2026, up 69.6% from $45.87 million a year earlier and up 25.5% from the prior quarter.
Analysis
Edap Tms (FOCL) Total Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Edap Tms came in at $59.58 million, up 23.5% from FY2024.
- Total Liabilities has now increased for four consecutive years, with a five-year compound annual growth rate of 11.0% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $48.27 million in FY2024 (+29.6%), $37.26 million in FY2023 (+18.1%), $31.55 million in FY2022 (+2.6%) and $30.75 million in FY2021 (-13.1%).
- The Q2 2026 figure marks the highest quarterly Total Liabilities in data going back to Q2 2009.
- Compared with a year earlier, Total Liabilities has increased for six straight quarters, with growth averaging 27.5% over the last seven quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q2 2026 (growth of 69.6%); the worst was Q4 2021 (a decline of 9.9%).
- Per Business Quant data, FOCL's Total Liabilities in the three quarters before Q2 2026 was $61.96 million (Q1 2026), $59.58 million (Q4 2025) and $44.59 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 3.14 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Edap Tms | 167.75 Mn | 100.27 Mn | 7.34 Mn | 77.77 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 77.77 Mn |
| Mar 31, 2026 | 61.96 Mn |
| Dec 31, 2025 | 59.58 Mn |
| Sep 30, 2025 | 44.59 Mn |
| Jun 30, 2025 | 45.87 Mn |
| Mar 31, 2025 | 42.62 Mn |
| Dec 31, 2024 | 48.27 Mn |
| Sep 30, 2024 | 39.98 Mn |
| Jun 30, 2024 | 37.19 Mn |
| Mar 31, 2024 | 39.21 Mn |
| Dec 31, 2023 | -48.74 Mn |
| Sep 30, 2023 | 36.12 Mn |
| Jun 30, 2023 | 34.97 Mn |
| Mar 31, 2023 | 36.29 Mn |
| Dec 31, 2022 | 30.09 Mn |
| Sep 30, 2022 | 30.81 Mn |
| Jun 30, 2022 | 30.98 Mn |
| Mar 31, 2022 | 28.83 Mn |
| Dec 31, 2021 | 31.08 Mn |
| Sep 30, 2021 | 30.24 Mn |
API Access
Edap Tms 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=FOCL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "FOCL", "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=FOCL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();