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ROLLINS, INC.: diluted weighted-average shares

Diluted weighted-average shares for ROLLINS, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All ROLLINS, INC. financial histories

What this measure means

Weighted-average shares used for diluted earnings per share. Potential shares are included under the applicable dilution rules, not simply added to outstanding shares.

Exact concept: us-gaap:WeightedAverageNumberOfDilutedSharesOutstanding. 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 2008-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Diluted weighted-average shares in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31484,147,000shares2026-02-1210-K · 0000084839-26-000008
2024-01-012024-12-31484,295,000shares2026-02-1210-K · 0000084839-26-000008
2023-01-012023-12-31490,130,000shares2026-02-1210-K · 0000084839-26-000008
2022-01-012022-12-31492,413,000shares2025-02-1310-K · 0000084839-25-000024
2021-01-012021-12-31492,054,000shares2024-02-1510-K · 0000084839-24-000025
2020-01-012020-12-31491,604,000shares2023-02-1610-K · 0000084839-23-000006
2019-01-012019-12-31491,216,000shares2022-02-2510-K · 0000084839-22-000011
2018-01-012018-12-31490,936,000shares2021-02-2610-K · 0001171200-21-000076
2017-01-012017-12-31326,982,000shares2020-02-2810-K · 0001171200-20-000103
2016-01-012016-12-31327,366,000shares2019-03-0110-K · 0001171200-19-000087
2015-01-012015-12-31218,583,000shares2018-02-2610-K · 0000084839-18-000065
2014-01-012014-12-31218,695,000shares2018-02-2610-K · 0000084839-18-000065
2013-01-012013-12-31219,121,000shares2016-02-2410-K · 0001552781-16-001318
2012-01-012012-12-31146,299shares2015-02-2510-K · 0001552781-15-000273
2011-01-012011-12-31146,882shares2014-02-2610-K · 0001552781-14-000153
2010-01-012010-12-31148,231,000shares2013-02-2710-K · 0001047469-13-001764
2009-01-012009-12-31149,624,000shares2012-02-2810-K · 0001047469-12-001690
2008-01-012008-12-31151,830,000shares2011-02-2510-K · 0001047469-11-001349

Related financial histories

Inspect the source

Entity
ROLLINS, INC. / CIK 0000084839
Captured
2026-09-19T14:51:52.132Z
SEC response SHA-256
ae4b8c87e5f58268ddf496d1e7eef6e01c40e4c1f9a6a5ab970f46e2b018263e

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/0000084839.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"])))