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CHECK POINT SOFTWARE TECHNOLOGIES LTD.: basic weighted-average shares

Basic weighted-average shares for CHECK POINT SOFTWARE TECHNOLOGIES LTD. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All CHECK POINT SOFTWARE TECHNOLOGIES LTD. financial histories

What this measure means

Time-weighted shares used for basic earnings per share. This denominator differs from shares outstanding at a single reporting date.

Exact concept: us-gaap:WeightedAverageNumberOfSharesOutstandingBasic. 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

Basic weighted-average shares in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31107,264,069shares2026-03-3120-F · 0001178913-26-001932
2024-01-012024-12-31110,617,625shares2026-03-3120-F · 0001178913-26-001932
2023-01-012023-12-31116,913,913shares2026-03-3120-F · 0001178913-26-001932
2022-01-012022-12-31125,205,504shares2025-03-1720-F · 0001178913-25-000867
2021-01-012021-12-31133,121,763shares2024-04-0220-F · 0001178913-24-001196
2020-01-012020-12-31140,495,886shares2023-04-2720-F · 0001193125-23-122355
2019-01-012019-12-31150,600,000shares2022-04-1420-F · 0001193125-22-105648
2018-01-012018-12-31156,600,000shares2021-04-0220-F · 0001193125-21-104893
2017-01-012017-12-31162,700,000shares2020-04-0220-F · 0001193125-20-095941
2016-01-012016-12-31170,155,000shares2019-04-2320-F · 0001193125-19-114952
2015-01-012015-12-31179,218,000shares2018-04-2720-F · 0001193125-18-138808
2014-01-012014-12-31188,487,000shares2017-04-2820-F · 0001193125-17-148090
2013-01-012013-12-31195,647,000shares2016-04-2820-F · 0001193125-16-564301
2012-01-012012-12-31203,918,000shares2015-04-2420-F · 0001193125-15-146312
2011-01-012011-12-31206,917,000shares2014-03-2820-F · 0001193125-14-121617
2010-01-012010-12-31208,106,000shares2013-03-1920-F · 0001193125-13-115148
2009-01-012009-12-31209,371,000shares2012-04-0920-F · 0001193125-12-155119

Related financial histories

Inspect the source

Entity
CHECK POINT SOFTWARE TECHNOLOGIES LTD. / CIK 0001015922
Captured
2026-09-20T05:12:57.355Z
SEC response SHA-256
34ca1832a7100e11f5e3e5fe58c94e6e46e9a230d46806d9f305e5453f632e49

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/0001015922.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"])))