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Cathay General Bancorp: diluted earnings per share

Diluted earnings per share for Cathay General Bancorp. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Cathay General Bancorp 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 2009-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Diluted earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-314.54USD/shares2026-03-0210-K · 0001437749-26-006157
2024-01-012024-12-313.95USD/shares2026-03-0210-K · 0001437749-26-006157
2023-01-012023-12-314.86USD/shares2026-03-0210-K · 0001437749-26-006157
2022-01-012022-12-314.83USD/shares2025-02-2810-K · 0001437749-25-005749
2021-01-012021-12-313.8USD/shares2024-02-2910-K · 0001437749-24-005948
2020-01-012020-12-312.87USD/shares2023-02-2810-K · 0001437749-23-004952
2019-01-012019-12-313.48USD/shares2022-03-0110-K · 0001437749-22-004752
2018-01-012018-12-313.33USD/shares2021-03-0110-K · 0001437749-21-004299
2017-01-012017-12-312.17USD/shares2020-03-0210-K · 0001437749-20-003977
2016-01-012016-12-312.19USD/shares2019-03-0410-K · 0001437749-19-003923
2015-01-012015-12-311.98USD/shares2018-03-0110-K · 0001437749-18-003646
2014-01-012014-12-311.72USD/shares2017-03-0110-K · 0001437749-17-003556
2013-01-012013-12-311.43USD/shares2016-02-2910-K · 0001437749-16-026345
2012-01-012012-12-311.28USD/shares2015-03-0210-K · 0001437749-15-003707
2011-01-012011-12-311.06USD/shares2014-03-0310-K · 0001437749-14-003147
2010-12-312011-12-311.06USD/shares2013-03-0110-K · 0001437749-13-002186
2010-01-012010-12-31-0.06USD/shares2012-02-2810-K · 0001193125-12-082651
2009-12-312010-12-31-0.06USD/shares2013-03-0110-K · 0001437749-13-002186
2009-01-012009-12-31-1.59USD/shares2012-02-2810-K · 0001193125-12-082651

Related financial histories

Inspect the source

Entity
Cathay General Bancorp / CIK 0000861842
Captured
2026-09-19T15:10:50.785Z
SEC response SHA-256
1a13dc8954d4baaac170c82788466e07a9884172b53cd3fbd9fe58161457e565

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/0000861842.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"])))