TG Therapeutics, Inc.: retained earnings or deficit
TG Therapeutics retained earnings or deficit: -$1.08 billion at 2025-12-31, up 29.2% on the year. 13 values since 2013, each linked to its SEC filing.
All TG Therapeutics, Inc. financial histories
At a glance
TG Therapeutics reported retained earnings or deficit of -$1.08 billion at 2025-12-31, up 29.2% from -$1.53 billion a year earlier. Across the last five reported years it ranged from -$1.55 billion (2023-12-31) to -$1.08 billion (2025-12-31).
Computed from the values in the table below, in USD; each links to the filing it came from.
What this measure means
Accumulated undistributed earnings or deficit at the reporting date. This balance is not cash available for distribution.
Exact concept: us-gaap:RetainedEarningsAccumulatedDeficit. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2013-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| - | 2025-12-31 | -1,082,015,000 | USD | 2026-02-27 | 10-K · 0001437749-26-006133 SEC |
| - | 2024-12-31 | -1,529,194,000 | USD | 2026-02-27 | 10-K · 0001437749-26-006133 SEC |
| - | 2023-12-31 | -1,552,577,000 | USD | 2025-03-03 | 10-K · 0001437749-25-005908 SEC |
| - | 2022-12-31 | -1,527,033,000 | USD | 2024-02-29 | 10-K · 0001437749-24-006144 SEC |
| - | 2021-12-31 | -1,328,698,000 | USD | 2023-03-01 | 10-K · 0001558370-23-002610 SEC |
| - | 2020-12-31 | -980,597,000 | USD | 2022-03-01 | 10-K · 0001558370-22-002617 SEC |
| - | 2019-12-31 | -701,216,000 | USD | 2021-03-01 | 10-K · 0001558370-21-002149 SEC |
| - | 2018-12-31 | -528,345,000 | USD | 2020-03-02 | 10-K · 0001558370-20-001897 SEC |
| - | 2017-12-31 | -354,863,000 | USD | 2019-03-01 | 10-K · 0001654954-19-002189 SEC |
| - | 2016-12-31 | -236,386,820 | USD | 2018-03-15 | 10-K · 0001654954-18-002638 SEC |
| - | 2015-12-31 | -158,133,926 | USD | 2017-03-16 | 10-K · 0001654954-17-002050 SEC |
| - | 2014-12-31 | -95,185,280 | USD | 2016-03-15 | 10-K · 0001144204-16-088155 SEC |
| - | 2013-12-31 | -39,404,003 | USD | 2015-03-16 | 10-K · 0001144204-15-016369 SEC |
Related TG THERAPEUTICS, INC. histories
Inspect the source
- Entity
- TG THERAPEUTICS, INC. / CIK 0001001316
- Captured
- SEC response SHA-256
153d276440c1903144d2ca193676af4b7014428a3e4b5524efe33528427880b3
Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON
Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.
Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.
Use this in research
A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.
These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.
Research methodology · Execution and cost assumptions · Check backtest overfitting
Build with the open-source tools
Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.
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- Read the MCP server source and integration examples
The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0001001316.json") as response:
record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
print(concept["tag"], next(iter(concept["observations"])))