TherapeuticsMD, Inc.: financing cash flow
TherapeuticsMD financing cash flow: $3.15 million for the year ending 2023-12-31. 12 values since 2011, each linked to its SEC filing. In original units.
All TherapeuticsMD, Inc. financial histories
At a glance
TherapeuticsMD reported financing cash flow of $3.15 million for the year ending 2023-12-31. From 2011 to 2023 it fell at a compound 3.3% a year, from $4.71 million to $3.15 million. Across the last five reported years it ranged from $3.15 million (2023-12-31) to $188.8 million (2019-12-31). That was 242.0% of revenue ($1.30 million) for the same year.
Computed from the values in the table below, in USD; each links to the filing it came from.
What this measure means
Net cash from financing activities, including borrowing, repayments and transactions with owners. A positive amount does not establish operating profitability.
Exact concept: us-gaap:NetCashProvidedByUsedInFinancingActivities. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2011-01-01 to 2023-12-31. The SEC response was captured on 2026-09-19.
This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2023-01-01 | 2023-12-31 | 3,151,000 | USD | 2025-03-27 | 10-K · 0001013762-25-003442 SEC |
| 2021-01-01 | 2021-12-31 | 129,552,000 | USD | 2022-03-23 | 10-K · 0001564590-22-011525 SEC |
| 2020-01-01 | 2020-12-31 | 80,725,000 | USD | 2022-03-23 | 10-K · 0001564590-22-011525 SEC |
| 2019-01-01 | 2019-12-31 | 188,827,000 | USD | 2022-03-23 | 10-K · 0001564590-22-011525 SEC |
| 2018-01-01 | 2018-12-31 | 162,787,087 | USD | 2021-03-04 | 10-K · 0001387131-21-003140 SEC |
| 2017-01-01 | 2017-12-31 | 72,584,249 | USD | 2020-02-24 | 10-K · 0001387131-20-002086 SEC |
| 2016-01-01 | 2016-12-31 | 137,225,535 | USD | 2019-02-27 | 10-K · 0001387131-19-001471 SEC |
| 2015-01-01 | 2015-12-31 | 92,973,228 | USD | 2018-02-23 | 10-K · 0001387131-18-000776 SEC |
| 2014-01-01 | 2014-12-31 | 43,298,099 | USD | 2017-02-28 | 10-K · 0001387131-17-001111 SEC |
| 2013-01-01 | 2013-12-31 | 73,989,416 | USD | 2016-02-26 | 10-K · 0001387131-16-004361 SEC |
| 2012-01-01 | 2012-12-31 | 14,436,885 | USD | 2015-03-12 | 10-K · 0001387131-15-000875 SEC |
| 2011-01-01 | 2011-12-31 | 4,707,714 | USD | 2014-03-05 | 10-K · 0001387131-14-000771 SEC |
Related TherapeuticsMD, Inc. histories
Inspect the source
- Entity
- TherapeuticsMD, Inc. / CIK 0000025743
- Captured
- SEC response SHA-256
566f636dfc852372b704143e2678a66d8d716f0795f8652994459dcc9f22859d
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.
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Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0000025743.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"])))