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Hydro One Inc.: diluted earnings per share

Diluted earnings per share for Hydro One Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Hydro One Inc. financial histories

What this measure means

Reported earnings or loss per share under dilution rules. Antidilutive instruments may be excluded. A diluted value can equal the basic value without implying no potential dilution.

Exact concept: us-gaap:EarningsPerShareDiluted. 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 2014-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.

Reading these values

This selected numerical history matches Basic earnings per share for the same reporting intervals and original units. The accounting definitions remain distinct. Equal values do not establish that the concepts are interchangeable or explain why they match; filing dates and accessions may differ. Compare the definitions and source filings before combining them.

Selected filing history

Diluted earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-319,519CAD/shares2026-02-1340-F · 0001628280-26-008011
2024-01-012024-12-318,254CAD/shares2026-02-1340-F · 0001628280-26-008011
2023-01-012023-12-317,677CAD/shares2025-02-2040-F · 0001114445-25-000007
2022-01-012022-12-317,431CAD/shares2023-02-1440-F · 0001114445-23-000009
2021-01-012021-12-316,834CAD/shares2023-02-1440-F · 0001114445-23-000009
2020-01-012020-12-3112,599CAD/shares2022-02-2540-F · 0001114445-22-000012
2019-01-012019-12-316,679CAD/shares2021-02-2540-F · 0001114445-21-000005
2018-01-012018-12-31-281CAD/shares2020-02-1240-F · 0001114445-20-000005
2017-01-012017-12-314,999CAD/shares2019-03-2840-F · 0001114445-19-000009
2016-01-012016-12-315,132CAD/shares2018-03-2940-F · 0001114445-18-000007
2015-01-012015-12-316,340CAD/shares2017-03-2740-F · 0001193125-17-097788
2014-01-012014-12-317,319CAD/shares2016-03-2240-F · 0001193125-16-512870

Related financial histories

Inspect the source

Entity
Hydro One Inc. / CIK 0001114445
Captured
2026-09-21T17:18:16.892Z
SEC response SHA-256
f570cb7ae09e5caed702fa0617829d01ee6306932969cff77ef28cf692d1e810

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/0001114445.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"])))