GENERAL DYNAMICS CORPORATION: 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

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

Inspect the source

Entity

GENERAL DYNAMICS CORPORATION / CIK 0000040533

Captured

2026-09-19T14:47:18.518Z

SEC response SHA-256

7fff513c1ae0c64ca16a673a15823a850bcb4d097506eaea38c8b540fa4708ff

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/0000040533.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"])))