PFIZER INC: diluted earnings per share

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

Selected filing history

Related financial histories

• PFIZER INC: total assets
• PFIZER INC: total liabilities
• PFIZER INC: stockholders equity
• PFIZER INC: cash and cash equivalents
• PFIZER INC: net income or loss
• PFIZER INC: operating cash flow
• PFIZER INC: capital expenditure payments
• PFIZER INC: revenue
• PFIZER INC: contract revenue excluding tax
• PFIZER INC: financing cash flow
• PFIZER INC: investing cash flow
• PFIZER INC: retained earnings or deficit
• PFIZER INC: basic weighted-average shares
• PFIZER INC: diluted weighted-average shares
• PFIZER INC: basic earnings per share
• PFIZER INC: income tax expense or benefit
• PFIZER INC: net property, plant and equipment
• PFIZER INC: share-based compensation expense
• PFIZER INC: current assets
• PFIZER INC: interest expense
• PFIZER INC: current liabilities
• PFIZER INC: current accounts payable
• PFIZER INC: goodwill carrying amount
• PFIZER INC: net finite-lived intangible assets
• PFIZER INC: net current accounts receivable
• PFIZER INC: common-stock repurchase payments
• PFIZER INC: net inventory
• PFIZER INC: selling, general and administrative expense

Inspect the source

Entity

PFIZER INC / CIK 0000078003

Captured

2026-09-19T14:51:02.160Z

SEC response SHA-256

bd072131f9dcf001f22e843fded5910c2c7fc178e2a739ce0c58b1934e84d566

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/0000078003.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"])))