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Concord Medical Services Holdings Ltd: diluted weighted-average shares

Diluted weighted-average shares for Concord Medical Services Holdings Ltd. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Concord Medical Services Holdings Ltd 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 2012-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Diluted weighted-average shares in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31131,053,858shares2026-04-2920-F · 0001104659-26-050692
2024-01-012024-12-31131,053,858shares2026-04-2920-F · 0001104659-26-050692
2023-01-012023-12-31131,053,858shares2026-04-2920-F · 0001104659-26-050692
2022-01-012022-12-31131,053,858shares2025-04-2520-F · 0001410578-25-000907
2021-01-012021-12-31131,053,858shares2024-04-1920-F · 0001104659-24-049117
2020-01-012020-12-31131,053,858shares2023-04-1920-F · 0001410578-23-000729
2016-01-012016-12-31130,631,867shares2017-05-0120-F · 0001144204-17-023641
2015-01-012015-12-31134,546,772shares2017-05-0120-F · 0001144204-17-023641
2014-01-012014-12-31135,180,642shares2017-05-0120-F · 0001144204-17-023641
2013-01-012013-12-31135,077,172shares2016-04-2820-F · 0001144204-16-097228
2012-01-012012-12-31138,211,177shares2015-04-2720-F · 0001193125-15-148374

Related financial histories

Inspect the source

Entity
Concord Medical Services Holdings Ltd / CIK 0001472072
Captured
2026-09-20T09:07:39.104Z
SEC response SHA-256
ed097c8b42d5c2284e8334be582446b3159955932b6f3073cd2302bae53d482c

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/0001472072.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"])))