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American National Group Inc.: investing cash flow

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

All American National Group 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 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Investing cash flow in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31-9,746,000,000USD2026-03-3110-K · 0001039828-26-000004
2024-01-012024-12-312,520,000,000USD2026-03-3110-K · 0001039828-26-000004
2023-01-012023-12-31-1,301,000,000USD2026-03-3110-K · 0001039828-26-000004
2022-01-012022-12-31-2,454,911,000USD2024-02-2910-K · 0001039828-24-000020
2021-01-012021-12-31-6,224,307,000USD2024-02-2910-K · 0001039828-24-000020
2020-01-012020-12-315,134,604,000USD2023-02-2810-K · 0001039828-23-000032
2019-01-012019-12-31-3,054,886,000USD2022-03-0110-K · 0001039828-22-000022
2018-01-012018-12-31-2,408,331,000USD2021-03-0110-K · 0001039828-21-000018
2017-01-012017-12-31-2,593,390,000USD2020-02-2510-K · 0001039828-20-000013
2016-01-012016-12-31-4,501,109,000USD2019-02-2210-K · 0001039828-19-000009
2015-01-012015-12-31-5,577,205,000USD2018-02-2310-K · 0001039828-18-000006
2014-01-012014-12-31-2,947,749,000USD2017-02-2710-K · 0001039828-17-000020
2013-01-012013-12-31-3,879,296,000USD2016-02-2610-K · 0001039828-16-000136
2012-01-012012-12-31-2,129,490,000USD2015-02-2710-K · 0001039828-15-000042
2011-01-012011-12-31-3,605,833,000USD2014-03-0310-K · 0001039828-14-000026
2010-01-012010-12-31-3,116,388,000USD2013-03-0710-K · 0001039828-13-000035
2009-01-012009-12-31-2,013,730,000USD2012-03-0110-K · 0001039828-12-000011

Related financial histories

Inspect the source

Entity
American National Group Inc. / CIK 0001039828
Captured
2026-09-20T05:15:41.343Z
SEC response SHA-256
f0aafc3c6b8c691aa3d100d9c741b63e8ef4f7c1fbbd70f8da3954b3e365abf6

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/0001039828.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"])))