Skip to content

FACTSET RESEARCH SYSTEMS INC.: investing cash flow

Investing cash flow for FACTSET RESEARCH SYSTEMS INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All FACTSET RESEARCH SYSTEMS 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 2008-09-01 to 2025-08-31. 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
2024-09-012025-08-31-392,773,000USD2025-10-2210-K · 0001628280-25-045769
2023-09-012024-08-31-144,317,000USD2025-10-2210-K · 0001628280-25-045769
2022-09-012023-08-31-95,393,000USD2025-10-2210-K · 0001628280-25-045769
2021-09-012022-08-31-2,033,675,000USD2024-10-2910-K · 0001013237-24-000141
2020-09-012021-08-31-135,992,000USD2023-10-2710-K · 0001013237-23-000128
2019-09-012020-08-31-73,632,000USD2022-10-2110-K · 0001013237-22-000159
2018-09-012019-08-31-56,100,000USD2021-10-2210-K · 0001013237-21-000142
2017-09-012018-08-31-48,531,000USD2020-10-2910-K · 0001013237-20-000153
2016-09-012017-08-31-347,306,000USD2019-10-3010-K · 0001437749-19-020894
2015-09-012016-08-31-158,408,000USD2018-10-3010-K · 0001437749-18-019028
2014-09-012015-08-31-64,877,000USD2017-10-3010-K · 0001437749-17-017840
2013-09-012014-08-31-70,708,000USD2016-10-3110-K · 0001437749-16-040606
2012-09-012013-08-31-20,412,000USD2015-11-0210-K · 0001437749-15-019227
2011-09-012012-08-31-58,849,000USD2014-10-3010-K · 0001437749-14-019084
2010-09-012011-08-31-29,343,000USD2013-10-3010-K · 0001437749-13-013610
2009-09-012010-08-31-75,948,000USD2012-10-3010-K · 0001437749-12-010651
2008-09-012009-08-311,220,000USD2011-10-3110-K · 0001193125-11-288590

Related financial histories

Inspect the source

Entity
FACTSET RESEARCH SYSTEMS INC. / CIK 0001013237
Captured
2026-09-20T05:12:29.125Z
SEC response SHA-256
a82da656084a714535a6e3d662af63d1c45b7560e9d9cdb4c1d7a8419bf410d1

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/0001013237.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"])))