THE BOEING COMPANY: net income or loss

What this measure means

Reported profit or loss for the period. Check the filing for attribution, exceptional items and discontinued operations before comparing companies.

Exact concept: us-gaap:NetIncomeLoss. 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

• THE BOEING COMPANY: total assets
• THE BOEING COMPANY: total liabilities
• THE BOEING COMPANY: stockholders equity
• THE BOEING COMPANY: cash and cash equivalents
• THE BOEING COMPANY: operating cash flow
• THE BOEING COMPANY: capital expenditure payments
• THE BOEING COMPANY: revenue
• THE BOEING COMPANY: contract revenue excluding tax
• THE BOEING COMPANY: financing cash flow
• THE BOEING COMPANY: investing cash flow
• THE BOEING COMPANY: retained earnings or deficit
• THE BOEING COMPANY: basic weighted-average shares
• THE BOEING COMPANY: diluted weighted-average shares
• THE BOEING COMPANY: basic earnings per share
• THE BOEING COMPANY: diluted earnings per share
• THE BOEING COMPANY: income tax expense or benefit
• THE BOEING COMPANY: net property, plant and equipment
• THE BOEING COMPANY: share-based compensation expense
• THE BOEING COMPANY: operating income or loss
• THE BOEING COMPANY: current assets
• THE BOEING COMPANY: current liabilities
• THE BOEING COMPANY: current accounts payable
• THE BOEING COMPANY: goodwill carrying amount
• THE BOEING COMPANY: net current accounts receivable
• THE BOEING COMPANY: common-stock repurchase payments
• THE BOEING COMPANY: gross profit
• THE BOEING COMPANY: cost of revenue
• THE BOEING COMPANY: research and development expense

Inspect the source

Entity

THE BOEING COMPANY / CIK 0000012927

Captured

2026-09-19T14:44:13.136Z

SEC response SHA-256

0c63f1ae7cc10b3c27e0c94f2add0c461e6293036dd4e52e52ae6dbb6f206e15

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/0000012927.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"])))