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Oncternal Therapeutics, Inc.: investing cash flow

Investing cash flow for Oncternal Therapeutics, Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Oncternal Therapeutics, Inc. financial histories

What this measure means

Net cash from investing activities, including asset purchases, disposals and investment transactions. This differs from capital expenditure payments alone.

Exact concept: us-gaap:NetCashProvidedByUsedInInvestingActivities. 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 2009-01-01 to 2023-12-31. The SEC response was captured on 2026-09-21.

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

Investing cash flow in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2023-01-012023-12-31651,000USD2024-03-0710-K · 0000950170-24-027984
2022-01-012022-12-31-26,498,000USD2024-03-0710-K · 0000950170-24-027984
2021-01-012021-12-310USD2023-03-0910-K · 0000950170-23-007062
2019-01-012019-12-3116,137,000USD2021-03-1210-K/A · 0001564590-21-012865
2018-01-012018-12-3127,883,000USD2019-03-1810-K · 0001047469-19-001382
2017-01-012017-12-31-15,126,000USD2019-03-1810-K · 0001047469-19-001382
2016-01-012016-12-312,151,000USD2019-03-1810-K · 0001047469-19-001382
2015-01-012015-12-3116,211,000USD2018-03-1310-K · 0001047469-18-001564
2014-01-012014-12-31-31,220,000USD2017-03-2410-K · 0001047469-17-001982
2013-01-012013-12-319,237,000USD2016-03-1510-K · 0001047469-16-011178
2012-01-012012-12-3121,405,000USD2015-03-1610-K · 0001047469-15-002283
2011-01-012011-12-31-10,299,000USD2014-03-1210-K · 0001104659-14-018791
2010-01-012010-12-318,280,000USD2013-03-0510-K · 0001047469-13-002200
2009-01-012009-12-31-9,425,000USD2012-03-0210-K · 0001193125-12-093770

Related financial histories

Inspect the source

Entity
Oncternal Therapeutics, Inc. / CIK 0001260990
Captured
2026-09-21T17:18:09.927Z
SEC response SHA-256
dcefea30a8ce148cff96c2a2fa09a3b61a34c7954f6f1a0e51956fda420a1d49

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.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001260990.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"])))