Dana Incorporated: selling, general and administrative expense

What this measure means

Selling and general administrative costs reported under this concept. It is an expense category, not a substitute for total operating expenses.

Exact concept: us-gaap:SellingGeneralAndAdministrativeExpense. 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 2009-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Related financial histories

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

Inspect the source

Entity

Dana Incorporated / CIK 0000026780

Captured

2026-09-19T14:45:44.822Z

SEC response SHA-256

e03de03b38cf9b9070c0dcb65ff1b305563e131d8bb6548a12248cb38ec59d5f

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/0000026780.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"])))