LogicMark (LGMK) Accumulated Expenses (2012 - 2026)
LogicMark (LGMK) posted Accumulated Expenses of $1.06 million for Q2 2026, up 17.3% from $902,736 a year earlier and up 4.2% from the prior quarter.
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Analysis
LogicMark (LGMK) Accumulated Expenses (2012 - 2026) Analysis & Trends
At the end of FY2025, LogicMark's Accumulated Expenses came in at $1.13 million, up 7.1% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of -3.0% (FY2020 to FY2025).
- In prior years, LogicMark's Accumulated Expenses was $1.05 million in FY2024 (-8.5%), $1.15 million in FY2023 (-33.9%), $1.74 million in FY2022 (+104.9%) and $849,285 in FY2021 (-35.4%).
- Quarterly Accumulated Expenses has run from a low of $750,532 in Q1 2023 to a high of $1.74 million in Q4 2022 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last five quarters, with growth averaging 1.5% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q4 2022, with growth of 104.9%; the weakest was Q2 2022, with a decline of 65.0%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $1.02 million (Q1 2026), $1.13 million (Q4 2025) and $1.25 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 248.22 Bn | 227.25 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 178.33 Bn | 148.76 Bn | 7.27 Bn |
| 3 | Danaher | 159.74 Bn | 143.54 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 158.45 Bn | 138.74 Bn | 2.08 Bn |
| 5 | Medtronic | 122.77 Bn | 88.02 Bn | 6.34 Bn |
| 6 | Stryker | 118.25 Bn | 104.37 Bn | 4.50 Bn |
| 7 | Boston Scientific | 66.98 Bn | 61.75 Bn | 3.85 Bn |
| 8 | Becton Dickinson | 54.49 Bn | 51.64 Bn | 2.32 Bn |
| 9 | Edwards Lifesciences | 51.67 Bn | 35.68 Bn | 1.35 Bn |
| 10 | LogicMark | 1.17 Mn | -26.52 Mn | 2.37 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.06 Mn |
| Mar 31, 2026 | 1.02 Mn |
| Dec 31, 2025 | 1.13 Mn |
| Sep 30, 2025 | 1.25 Mn |
| Jun 30, 2025 | 902,736.00 |
| Mar 31, 2025 | 890,473.00 |
| Dec 31, 2024 | 1.05 Mn |
| Sep 30, 2024 | 1.25 Mn |
| Jun 30, 2024 | 767,717.00 |
| Mar 31, 2024 | 1.54 Mn |
| Dec 31, 2023 | 1.15 Mn |
| Sep 30, 2023 | 1.21 Mn |
| Jun 30, 2023 | 847,637.00 |
| Mar 31, 2023 | 750,532.00 |
| Dec 31, 2022 | 1.74 Mn |
| Sep 30, 2022 | 1.05 Mn |
| Jun 30, 2022 | 862,223.00 |
| Mar 31, 2022 | 766,313.00 |
| Dec 31, 2021 | 849,285.00 |
| Sep 30, 2021 | 1.66 Mn |
API Access
LogicMark Accumulated Expenses 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=accumulated-expenses&ticker=LGMK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "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=accumulated-expenses&ticker=LGMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();