AMERICAN INTERNATIONAL GROUP, INC.: diluted weighted-average shares

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 2007-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Related financial histories

• AMERICAN INTERNATIONAL GROUP, INC.: total assets
• AMERICAN INTERNATIONAL GROUP, INC.: total liabilities
• AMERICAN INTERNATIONAL GROUP, INC.: stockholders equity
• AMERICAN INTERNATIONAL GROUP, INC.: net income or loss
• AMERICAN INTERNATIONAL GROUP, INC.: operating cash flow
• AMERICAN INTERNATIONAL GROUP, INC.: revenue
• AMERICAN INTERNATIONAL GROUP, INC.: financing cash flow
• AMERICAN INTERNATIONAL GROUP, INC.: investing cash flow
• AMERICAN INTERNATIONAL GROUP, INC.: retained earnings or deficit
• AMERICAN INTERNATIONAL GROUP, INC.: basic weighted-average shares
• AMERICAN INTERNATIONAL GROUP, INC.: basic earnings per share
• AMERICAN INTERNATIONAL GROUP, INC.: diluted earnings per share
• AMERICAN INTERNATIONAL GROUP, INC.: income tax expense or benefit
• AMERICAN INTERNATIONAL GROUP, INC.: net property, plant and equipment
• AMERICAN INTERNATIONAL GROUP, INC.: interest expense
• AMERICAN INTERNATIONAL GROUP, INC.: goodwill carrying amount
• AMERICAN INTERNATIONAL GROUP, INC.: common-stock repurchase payments
• AMERICAN INTERNATIONAL GROUP, INC.: selling, general and administrative expense

Inspect the source

Entity

AMERICAN INTERNATIONAL GROUP, INC. / CIK 0000005272

Captured

2026-09-19T14:43:08.045Z

SEC response SHA-256

f0345bdab4c5d99fd3fc9d0fdf2fe7d72787367ee0fbb4ed5b603a9e8fa730f0

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.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000005272.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"])))