LogicMark (LGMK) Retained Earnings (2012 - 2026)
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Analysis
LogicMark (LGMK) Retained Earnings (2012 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Retained Earnings (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 241.25 Bn | 220.40 Bn | 4.88 Bn | 62.19 Bn |
| 2 | Abbott Laboratories | 167.33 Bn | 138.41 Bn | 7.27 Bn | 49.79 Bn |
| 3 | Danaher | 148.83 Bn | 132.65 Bn | 3.61 Bn | 48.23 Bn |
| 4 | Intuitive Surgical | 142.00 Bn | 121.55 Bn | 1.96 Bn | 6.84 Bn |
| 5 | Medtronic | 110.70 Bn | 76.57 Bn | 6.34 Bn | 33.19 Bn |
| 6 | Stryker | 104.72 Bn | 90.84 Bn | 4.50 Bn | 21.82 Bn |
| 7 | Boston Scientific | 62.66 Bn | 57.67 Bn | 3.85 Bn | 7.82 Bn |
| 8 | Edwards Lifesciences | 49.13 Bn | 33.24 Bn | 1.35 Bn | 14.86 Bn |
| 9 | Becton Dickinson | 48.51 Bn | 45.66 Bn | 2.32 Bn | 17.51 Bn |
| 10 | LogicMark | 989,734.92 | -26.70 Mn | 2.37 Mn | -119.64 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -119.64 Mn |
| Mar 31, 2026 | -118.08 Mn |
| Dec 31, 2025 | -116.63 Mn |
| Sep 30, 2025 | -115.03 Mn |
| Jun 30, 2025 | -113.41 Mn |
| Mar 31, 2025 | -111.36 Mn |
| Dec 31, 2024 | -109.16 Mn |
| Sep 30, 2024 | -105.46 Mn |
| Jun 30, 2024 | -103.94 Mn |
| Mar 31, 2024 | -101.91 Mn |
| Dec 31, 2023 | -100.16 Mn |
| Sep 30, 2023 | -91.16 Mn |
| Jun 30, 2023 | -89.71 Mn |
| Mar 31, 2023 | -87.44 Mn |
| Dec 31, 2022 | -85.61 Mn |
| Sep 30, 2022 | -83.18 Mn |
| Jun 30, 2022 | -81.08 Mn |
| Mar 31, 2022 | -79.95 Mn |
| Dec 31, 2021 | -78.66 Mn |
| Sep 30, 2021 | -72.36 Mn |
API Access
LogicMark Retained Earnings 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=retained-earnings&ticker=LGMK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "retained-earnings", "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=retained-earnings&ticker=LGMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();