LogicMark (LGMK) Total Liabilities (2012 - 2026)
LogicMark (LGMK) recorded Total Liabilities of $3.84 million in Q2 2026, down 5.3% from $4.06 million a year earlier but up 4.7% from the prior quarter.
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Analysis
LogicMark (LGMK) Total Liabilities (2012 - 2026) Analysis & Trends
At the end of FY2025, LogicMark reported Total Liabilities of $4.02 million, up 4.9% from FY2024.
- Annual Total Liabilities has a five-year compound annual growth rate of -25.7% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $3.84 million in FY2024 (-1.9%), $3.91 million in FY2023 (-16.1%), $4.66 million in FY2022 (+31.9%) and $3.53 million in FY2021 (-80.1%).
- Quarterly Total Liabilities has ranged from -$25.55 million in Q1 2022 to $5.98 million in Q3 2021 over the past five years.
- On a year-over-year basis, Total Liabilities rose in three of the last eight quarters, with growth averaging 2.4%.
- Peak year-over-year performance for Total Liabilities in the last five years was growth of 31.9% in Q4 2022, against a decline of 80.1% in Q4 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $3.67 million (Q1 2026), $4.02 million (Q4 2025) and $4.54 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 247.86 Bn | 226.89 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 177.43 Bn | 147.86 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 159.54 Bn | 143.35 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 157.40 Bn | 137.68 Bn | 2.08 Bn | 3.23 Bn |
| 5 | Medtronic | 122.54 Bn | 87.79 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 117.68 Bn | 103.80 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 66.64 Bn | 61.41 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Becton Dickinson | 54.28 Bn | 51.43 Bn | 2.32 Bn | 26.32 Bn |
| 9 | Edwards Lifesciences | 51.48 Bn | 35.49 Bn | 1.35 Bn | 3.14 Bn |
| 10 | LogicMark | 1.17 Mn | -26.52 Mn | 2.37 Mn | 3.84 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.84 Mn |
| Mar 31, 2026 | 3.67 Mn |
| Dec 31, 2025 | 4.02 Mn |
| Sep 30, 2025 | 4.54 Mn |
| Jun 30, 2025 | 4.06 Mn |
| Mar 31, 2025 | 4.01 Mn |
| Dec 31, 2024 | 3.84 Mn |
| Sep 30, 2024 | 3.69 Mn |
| Jun 30, 2024 | 3.41 Mn |
| Mar 31, 2024 | 4.07 Mn |
| Dec 31, 2023 | 3.91 Mn |
| Sep 30, 2023 | 4.12 Mn |
| Jun 30, 2023 | 3.51 Mn |
| Mar 31, 2023 | 3.50 Mn |
| Dec 31, 2022 | 4.66 Mn |
| Sep 30, 2022 | 4.52 Mn |
| Jun 30, 2022 | 3.81 Mn |
| Mar 31, 2022 | -25.55 Mn |
| Dec 31, 2021 | 3.53 Mn |
| Sep 30, 2021 | 5.98 Mn |
API Access
LogicMark 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=LGMK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "LGMK", "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=LGMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();