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NATIONAL HEALTHCARE CORP: diluted earnings per share

Diluted earnings per share for NATIONAL HEALTHCARE CORP. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All NATIONAL HEALTHCARE CORP 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 2026-09-20.

Selected filing history

Diluted earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-317.67USD/shares2026-02-2610-K · 0001437749-26-005910
2024-01-012024-12-316.53USD/shares2026-02-2610-K · 0001437749-26-005910
2023-01-012023-12-314.34USD/shares2026-02-2610-K · 0001437749-26-005910
2022-01-012022-12-311.45USD/shares2025-03-0310-K/A · 0001437749-25-005928
2021-01-012021-12-318.99USD/shares2024-02-1610-K · 0001437749-24-004619
2020-01-012020-12-312.72USD/shares2023-02-1710-K · 0001437749-23-003830
2019-01-012019-12-314.44USD/shares2022-02-1810-K · 0001437749-22-003787
2018-01-012018-12-313.87USD/shares2021-02-1910-K · 0001437749-21-003415
2017-01-012017-12-313.69USD/shares2020-02-2110-K · 0001437749-20-003248
2016-01-012016-12-313.32USD/shares2019-02-2010-K · 0001437749-19-002958
2015-01-012015-12-313.2USD/shares2018-02-2010-K · 0001437749-18-002879
2014-01-012014-12-313.14USD/shares2017-02-1510-K · 0001047335-17-000042
2013-01-012013-12-313.87USD/shares2016-02-1910-K · 0001047335-16-000180
2012-01-012012-12-313.57USD/shares2015-02-2010-K · 0001047335-15-000018
2011-01-012011-12-313.96USD/shares2014-02-2110-K · 0001047335-14-000023
2010-01-012010-12-313.22USD/shares2013-08-2310-K/A · 0001047335-13-000094
2009-01-012009-12-312.31USD/shares2012-02-1710-K/A · 0001047335-12-000019

Related financial histories

Inspect the source

Entity
NATIONAL HEALTHCARE CORP / CIK 0001047335
Captured
2026-09-20T05:16:48.792Z
SEC response SHA-256
9c3ea67de396a939aced4fe07208413dd480336d3699f0e8528f4594e302cb2c

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/0001047335.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"])))